Publications

Revues

  • [DOI] X. Li, Q. Meng, W. Li, C. Zhang, T. Jancso, and S. Mavromatis, “An explorative study on the proximity of buildings to green spaces in urban areas using remotely sensed imagery,” Annals of gis, vol. 20, iss. 3, p. 193–203, 2014.
    [Bibtex]
    @article{li2014explorative,
    title = { An explorative study on the proximity of buildings to green spaces in urban areas using remotely sensed imagery },
    author = { Li, Xiaojiang and Meng, Qingyan and Li, Weidong and Zhang, Chuanrong and Jancso, Tamas and Mavromatis, S{\'e}bastien },
    journal = { Annals of GIS },
    volume = { 20 },
    number = { 3 },
    pages = { 193--203 },
    year = { 2014 },
    publisher = { Taylor \& Francis },
    doi = { 10.1080/19475683.2014.945482 },
    URL = { http://dx.doi.org/10.1080/19475683.2014.945482 },
    eprint = { http://dx.doi.org/10.1080/19475683.2014.945482 },
    abstract = { Urban areas are major places where intensive interactions between human and the natural system occur. Urban vegetation is a major component of the urban ecosystem, and urban residents benefit substantially from urban green spaces. To measure urban green spaces, remote sensing is an established tool due to its capability of monitoring urban vegetation quickly and continuously. In this study: (1) a Building's Proximity to Green spaces Index (BPGI) was proposed as a measure of building's neighbouring green spaces; (2) LiDAR data and multispectral remotely sensed imagery were used to automatically extract information regarding urban buildings and vegetation; (3) BPGI values for all buildings were calculated based on the extracted data and the proximity and adjacency of buildings to green spaces; and (4) two districts were selected in the study area to examine the relationships between the BPGI and different urban environments. Results showed that the BPGI could be used to evaluate the proximity of residents to green spaces at building level, and there was an obvious disparity of BPGI values and distribution of BPGI values between the two districts due to their different urban functions (i.e., downtown area and residential area). Since buildings are the major places for residents to live, work and entertain, this index may provide an objective tool for evaluating the proximity of residents to neighbouring green spaces. However, it was suggested that proving correlations between the proposed index and human health or environmental amenity would be important in future research for the index to be useful in urban planning. },
    x-audience = { international },
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • [DOI] X. Li, Q. Meng, X. Gu, T. Jancso, T. Yu, K. Wang, and S. Mavromatis, “A hybrid method combining pixel-based and object-oriented methods and its application in hungary using chinese hj-1 satellite images,” International journal of remote sensing, vol. 34, iss. 13, p. 4655–4668, 2013.
    [Bibtex]
    @article{li2013hybrid,
    title = { A hybrid method combining pixel-based and object-oriented methods and its application in Hungary using Chinese HJ-1 satellite images },
    author = { Li, Xiaojiang and Meng, Qingyan and Gu, Xingfa and Jancso, Tamas and Yu, Tao and Wang, Ke and Mavromatis, S{\'e}bastien },
    journal = { International Journal of Remote Sensing },
    volume = { 34 },
    number = { 13 },
    pages = { 4655--4668 },
    year = { 2013 },
    publisher = { Taylor \& Francis },
    doi = { 10.1080/01431161.2013.780669 },
    URL = { http://dx.doi.org/10.1080/01431161.2013.780669 },
    eprint = { http://dx.doi.org/10.1080/01431161.2013.780669 },
    abstract = { Pixel-based and object-oriented processing of Chinese HJ-1-A satellite imagery (resolution 30 m) acquired on 23 July 2009 were utilized for classification of a study area in Budapest, Hungary. The pixel-based method (maximum likelihood classifier for pixel-level method (MLCPL)) and two object-oriented methods (maximum likelihood classifier for object-level method (MLCOL) and a hybrid method combining image segmentation with the use of a maximum likelihood classifier at the pixel level (MLCPL)) were compared. An extension of the watershed segmentation method was used in this article. After experimenting, we chose an optimum segmentation scale. Classification results showed that the hybrid method outperformed MLCOL, with an overall accuracy of 90.53\%, compared with the overall accuracy of 77.53\% for MLCOL. Jeffries-Matusita distance analysis revealed that the hybrid method could maintain spectral separability between different classes, which explained the high classification accuracy in mixed-cover types compared with MLCOL. The classification result of the hybrid model is preferred over MLCPL in geographical or landscape ecological research for its accordance with patches in landscape ecology, and for continuity of results. The hybrid of image segmentation and pixel-based classification provides a new way to classify land-cover types, especially mixed land-cover types, using medium-resolution images on a regional, national, or global basis. },
    x-audience = { international },
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • C. Palmann, S. Mavromatis, and J. Sequeira, “Mesure de similarité entre sous-parties de nuages de points 2d,” Ts. traitement du signal, vol. 29, iss. 1-2, p. 29–49, 2012.
    [Bibtex]
    @article{palmann2012mesure,
    title = { Mesure de similarit{\'e} entre sous-parties de nuages de points 2D },
    author = { Palmann, Christophe and Mavromatis, S{\'e}bastien and Sequeira, Jean },
    journal = { TS. Traitement du signal },
    volume = { 29 },
    number = { 1-2 },
    pages = { 29--49 },
    year = { 2012 },
    publisher = { Lavoisier },
    abstract = { This communication focuses on the characterisation of a similarity measure between parts of 2D point clouds. This measure is defined thanks to the use of a general knowledge about real point clouds: they share a large amount of one-dimensional structures. These structures can be represented into a unified manner with a new type of primitives; then, we set the link between the existence of common information between parts of point clouds and the geometric relations of their primitives. Thus, we define a similarity measure that is rotationally invariant, and an algorithm to compute it. },
    x-audience = { international },
    x-peerreviewing = Yes,
    x-language = { fr },
    x-popularlevel = NO
    }
  • [DOI] C. Palmann, S. Mavromatis, M. Hernández, J. Sequeira, and B. Brisco, “Earth observation using radar data: an overview of applications and challenges,” International journal of digital earth, vol. 1, iss. 2, p. 171–195, 2008.
    [Bibtex]
    @article{palmann2008earth,
    title = { Earth observation using radar data: an overview of applications and challenges },
    author = { Palmann, Christophe and Mavromatis, S{\'e}bastien and Hern{\'a}ndez, Mario and Sequeira, Jean and Brisco, Brian },
    journal = { International Journal of Digital Earth },
    volume = { 1 },
    number = { 2 },
    pages = { 171--195 },
    year = { 2008 },
    publisher = { Taylor \& Francis },
    doi = { 10.1080/17538940802038317 },
    URL = { http://dx.doi.org/10.1080/17538940802038317 },
    eprint = { http://dx.doi.org/10.1080/17538940802038317 },
    abstract = { The first pictures of the earth were taken from a balloon in the mid-19th century and thus started 'earth observation'. Aerial missions in the 20th century enabled the build-up of outstanding photographic libraries and then with Landsat-1, the first civilian satellite launched in 1972, digital images of the earth became an operational reality. The main roles of earth observation have become scientific, economic and strategic, and the role of synthetic aperture radar (SAR) is significant in this overall framework. Radar image exploitation has matured and several operational programs regularly use SAR data for input and numerous applications are being further developed. The technological development of interferometry and polarimetry has helped further develop these radar based applications. This paper highlights this role through a description of actual applications and projects, and concludes with a discussion of some challenges for which SAR systems may provide significant assistance. },
    x-audience = { international },
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • [DOI] G. Poplu, H. Ripoll, S. Mavromatis, and J. Baratgin, “How do expert soccer players encode visual information to make decisions in simulated game situations?,” Research quarterly for exercise and sport, vol. 79, iss. 3, p. 392–398, 2008.
    [Bibtex]
    @article{poplu2008expert,
    title = { How do expert soccer players encode visual information to make decisions in simulated game situations? },
    author = { Poplu, G{\'e}rald and Ripoll, Hubert and Mavromatis, S{\'e}bastien and Baratgin, Jean },
    journal = { Research quarterly for exercise and sport },
    volume = { 79 },
    number = { 3 },
    pages = { 392--398 },
    year = { 2008 },
    publisher = { Taylor \& Francis },
    doi = {10.1080/02701367.2008.10599503 },
    URL = { http://www.tandfonline.com/doi/abs/10.1080/02701367.2008.10599503 },
    eprint = { http://www.tandfonline.com/doi/pdf/10.1080/02701367.2008.10599503 },
    abstract = { The aim of this study was to determine what visual information expert soccer players encode when they are asked to make a decision. We used a repetition-priming paradigm to test the hypothesis that experts encode a soccer pattern's structure independently of the players' physical characteristics (i.e., posture and morphology). The participants were given either realistic (digital photos) or abstract (three-dimensional schematic representations) soccer game patterns. The results showed that the experts benefited from priming effects regardless of how abstract the stimuli were. This suggests that an abstract representation of a realistic pattern (i.e., one that does not include visual information related to the players' physical characteristics) is sufficient to activate experts' specific knowledge during decision making. These results seem to show that expert soccer players encode and store abstract representations of visual patterns in memory. },
    x-audience = { international },
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • S. Mavromatis, J. Boï, R. Bulot, and J. Sequeira, “Texture analysis using directional local extrema,” Machine graphics & vision international journal, vol. 13, iss. 3, p. 289–302, 2004.
    [Bibtex]
    @article{mavromatis2004texture,
    title = { Texture analysis using directional local extrema },
    author = { Mavromatis, S{\'e}bastien and Boï, Jean-Marc and Bulot, R{\'e}my and Sequeira, Jean },
    journal = { Machine Graphics \& Vision International Journal },
    volume = { 13 },
    number = { 3 },
    pages = { 289--302 },
    year = { 2004 },
    issn = { 1230-0535 },
    publisher = { Polish Academy of Sciences },
    abstract = { In this paper, we propose a new formalism that enables to take into account textural features of the image in a very robust and selective way. This approach also permits visualization of these features so experts can efficiently supervise an image segmentation process based on texture analysis. The texture concept has been studied through different approaches. One of them is based on the notion of ordered local extrema and is very promising. Unfortunately, this approach does not take into account texture directionality; and the mathematical morphology formalism, on which it is based, does not enable extensions to this feature. This has led us to design a new formalism for texture representation capable of including directionality features. It produces a representation of texture-relevant features in the form of a surface z = f(x, y). The visualization of this surface gives experts sufficient information for discriminating different textures. We illustrate this approach by a set of results showing its interest in the frame of supervised image segmentation. },
    x-audience = { international },
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • [DOI] G. Poplu, J. Baratgin, S. Mavromatis, and H. Ripoll, “What kind of processes underlie decision making in soccer simulation? an implicit-memory investigation.,” International journal of sport and exercise psychology, vol. 1, iss. 4, p. 390–405, 2003.
    [Bibtex]
    @article{poplu2003kind,
    title = { What kind of processes underlie decision making in soccer simulation? An implicit-memory investigation. },
    author = { Poplu, G{\'e}rald and Baratgin, Jean and Mavromatis, S{\'e}bastien and Ripoll, Hubert },
    journal = { International Journal of Sport and Exercise Psychology },
    volume = { 1 },
    number = { 4 },
    pages = { 390--405 },
    year = { 2003 },
    publisher = { Taylor \& Francis },
    doi = {10.1080/1612197X.2003.9671727},
    URL = { http://dx.doi.org/10.1080/1612197X.2003.9671727 },
    eprint = { http://dx.doi.org/10.1080/1612197X.2003.9671727 },
    abstract = { Abstract Many researchers have used simulation to study the cognitive processes that underlie the decision-making skills of expert athletes. However, we have seen that these studies used an explicit‐memory paradigm that does not uncover the processes responsible for the emergence of decisions made during a game. They have primarily been concerned with describing elementary operations rather than with identifying the nature of the processes involved. We therefore chose a priming paradigm, in an attempt to identify the decision-making processes implemented during a simulated game. The results showed that the nature of the processing depended on the characteristics of the decision-making task being considered. When the task required a one-step decision, low-level processes were utilized; when it required a series of planned actions, expert players implemented high-level processes. },
    x-audience = { international },
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • S. Mavromatis and J. Sequeira, “3d medical imaging: from 2d images to 3d models,” Journal of medical informatics & technologies, vol. 3, p. 7–15, 2002.
    [Bibtex]
    @article{mavromatis20023d,
    title = { 3D medical imaging: from 2D images to 3D models },
    author = { Mavromatis, S{\'e}bastien and Sequeira, Jean },
    journal = { Journal of Medical Informatics \& Technologies },
    volume = { 3 },
    pages = { 7--15 },
    year = { 2002 },
    abstract = { Up to the end of the 70's, Medical Imaging was mainly related to the study of planar data sets resulting from direct physical acquisitions (e.g. X-Ray radiographs). Then, the development of inverse methods associated with the increasing power of computers enabled the visualization and the analysis of human being cross-section images (e.g. CT scans, MRI): these images are the result of mathematical processes and do not present direct physical acquisitions. The visualization of these data in three-dimensional space was made possible by the use of a set of parallel cross-sections: the result was spectacular but not sufficient for further development, especially in the case of clinical applications. Such applications need the characterization of a geometrical model, e.g. for the capture of sophisticated geometrical parameters or to provide a mathematical support to mechanical simulations. },
    x-audience = { international },
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }

Brevets

  • S. Mavromatis and J. Sequeira, “Method and system for estimating a similarity between two binary images,” , iss. WO Patent 2012117210A1, 2014-01-01.
    [Bibtex]
    @patent{mavromatis2014method,
    title={ Method and system for estimating a similarity between two binary images },
    author={ Mavromatis, S{\'e}bastien and Sequeira, Jean },
    year={ 2014-01-01 },
    abstract = { Method and system for estimating a similarity between two binary images. },
    x-country={ FR },
    x-audience = { International },
    x-language = { en },
    number={ WO Patent 2012117210A1 }
    }
  • S. Mavromatis and J. Sequeira, “Procédé et système pour estimer une similarité entre deux images binaires,” , iss. EP Patent PCT/FR2012/050,438, 2012-01-01.
    [Bibtex]
    @patent{mavromatis2012procede,
    title={ Proc{\'e}d{\'e} et syst{\`e}me pour estimer une similarit{\'e} entre deux images binaires },
    author={ Mavromatis, S{\'e}bastien and Sequeira, Jean },
    year={ 2012-01-01 },
    abstract = { Method and system for estimating a similarity between two binary images. },
    x-country={ FR },
    x-audience = { Nationale },
    x-language = { fr },
    number={ EP Patent PCT/FR2012/050,438 }
    }

Chapitre de livre

  • S. Mavromatis and J. Sequeira, “3d reconstruction of sport scenes,” in 3d video: from capture to diffusion, John Wiley & Sons, Inc., 2013, p. 405–420.
    [Bibtex]
    @incollection{mavromatis20133d,
    title = { 3D Reconstruction of Sport Scenes },
    author = { Mavromatis, S{\'e}bastien and Sequeira, Jean },
    booktitle = { 3D Video: From Capture to Diffusion },
    pages = { 405--420 },
    year = { 2013 },
    abstract = { In this chapter, the authors present the key stages of the reconstruction process, focusing on certain difficult points. They consider the analysis of color images with the aim of automatically selecting the playing surface. The region of interest (ROI) of a sporting scene is, naturally, the playing area. This playing area may often be characterized both as a region with a relatively uniform shade and as the largest quasi-connected component of the image under consideration. They concern the extraction of markings on the playing field using Hough transforms. For sporting scenes, pitch markings are often made up of straight and ellipse arc segments, and the Hough transform is ideally suited to characterizing these simple geometric primitives. They consider the matching of primitives extracted from images with those used in the model of the scene. },
    publisher = { John Wiley \& Sons, Inc. },
    x-audience = { International },
    x-language = { en },
    x-popularlevel = No
    }
  • S. Mavromatis and J. Sequeira, “Reconstruction 3d de scènes sportives,” in Vidéo 3d : capture, traitement et diffusion, Hermès – Lavoisier, 2013, p. 217–232.
    [Bibtex]
    @incollection{mavromatis2013reconstruction,
    title = { Reconstruction 3D de sc{\`e}nes sportives },
    author = { Mavromatis, S{\'e}bastien and Sequeira, Jean },
    booktitle = { Vid{\'e}o 3D : Capture, traitement et diffusion },
    pages = { 217--232 },
    year = { 2013 },
    abstract = { Ce chapitre pr{\'e}sente les {\'e}tapes cl{\'e}s du processus de reconstruction en se focalisant sur certains "points difficiles". Une premi{\'e}re partie traite de l'analyse d'images couleur en vue de s{\'e}lectionner automatiquement la surface de jeu. Dans une seconde partie, l'extraction du marquage dans l'aire de jeu sera abord{\'e}e en s'appuyant sur l'utilisation de la transform{\'e}e de Hough. Une troisi{\`e}me et derni{\`e}re partie traite de la mise en correspondance des primitives extraites des images avec celles du mod{\`e}le de la sc{\`e}ne. },
    publisher = { Herm{\`e}s - Lavoisier },
    x-audience = { National },
    x-language = { fr },
    x-popularlevel = No
    }

Conférences

  • A. Chergui, S. Ouchtati, S. Mavromatis, and J. Sequeira, “Investigating deep cnns models applied in kinship verification through facial images,” in 5th international conference on frontiers of signal processing, icfsp, Marseille, France, 2019.
    [Bibtex]
    @inproceedings{mavromatis2019-4,
    keywords = {perso, Algerie},
    TITLE = {Investigating Deep CNNs Models Applied in Kinship Verification through Facial Images},
    AUTHOR = {Chergui, Abdelhakim and Ouchtati, Salim and Mavromatis, S{\'e}bastien and Sequeira, Jean},
    BOOKTITLE = {5th International Conference on Frontiers of Signal Processing, ICFSP},
    YEAR = {2019},
    MONTH = {September},
    ADDRESS = {Marseille, France}
    }
  • A. Chergui, S. Ouchtati, S. Mavromatis, S. E. Bekhouche, and J. Sequeira, “Kinship verification using mixed descriptors and multi block face representation,” in 4th international conference on networking and advanced systems, icnas, Annaba, Algeria, 2019.
    [Bibtex]
    @inproceedings{mavromatis2019-3,
    keywords = {perso, Algerie},
    TITLE = {Kinship Verification using Mixed Descriptors and Multi Block Face Representation},
    AUTHOR = {Chergui, Abdelhakim and Ouchtati, Salim and Mavromatis, S{\'e}bastien and Bekhouche, Salah Eddine and Sequeira, Jean},
    BOOKTITLE = {4th International Conference on Networking and Advanced Systems, ICNAS},
    YEAR = {2019},
    MONTH = {June},
    ADDRESS = {Annaba, Algeria}
    }
  • R. Girard, S. Mavromatis, J. Sequeira, N. Belanger, and G. Anoufa, “A vision-based assistance key differenciator for helicopters automonous scalable missions,” in 20th towards autonomous robotic systems conference, taros, London, England, 2019.
    [Bibtex]
    @inproceedings{mavromatis2019-AH-2,
    keywords = {perso, these_RG},
    TITLE = {A vision-based assistance key differenciator for helicopters automonous scalable missions},
    AUTHOR = {Girard, Rémi and Mavromatis, S{\'e}bastien and Sequeira, Jean and Belanger, Nicolas and Anoufa, Guillaume},
    BOOKTITLE = {20th Towards Autonomous Robotic Systems Conference, TAROS},
    YEAR = {2019},
    MONTH = {July},
    ADDRESS = {London, England}
    }
  • A. Monneau, K. N. M’Sirdi, S. Mavromatis, G. Varra, M. Salesse, and J. Sequeira, “Adaptive prediction for ship motion in rotorcraft maritime operations,” in 5th ceas conference on guidance, navigation and control – eurognc19, Milan, Italy, 2019.
    [Bibtex]
    @inproceedings{mavromatis2019-AH-1,
    keywords = {perso, these_AM},
    TITLE = {Adaptive Prediction for Ship Motion in Rotorcraft Maritime Operations},
    AUTHOR = {Monneau, Antoine and M'Sirdi, Kouider Nacer and Mavromatis, S{\'e}bastien and Varra, Guillaume and Salesse, Marc and Sequeira, Jean},
    BOOKTITLE = {5th CEAS Conference on Guidance, Navigation and Control - EuroGNC19},
    YEAR = {2019},
    MONTH = {Apr},
    ADDRESS = {Milan, Italy}
    }
  • P. Zoppitelli, S. Mavromatis, J. Sequeira, G. Anoufa, Belanger Nicolas, and F. Fillias, “Embedding intelligent image processing algorithms: the new safety enhancer for helicopters missions,” in 44th european rotorcraft forum – erf 2018, Delft, Netherlands, 2018.
    [Bibtex]
    @inproceedings{mavromatis2018-AH,
    keywords = {perso, these_PZ},
    TITLE = {Embedding intelligent image processing algorithms: the new safety enhancer for helicopters missions},
    AUTHOR = {Zoppitelli, Pierre and Mavromatis, S{\'e}bastien and Sequeira, Jean and Anoufa, Guillaume and Belanger, Nicolas, and Fillias, Francois-Xavier},
    BOOKTITLE = {44th European Rotorcraft Forum - ERF 2018},
    YEAR = {2018},
    MONTH = {Sep},
    ADDRESS = {Delft, Netherlands}
    }
  • [DOI] D. Huang, Y. Wang, W. Song, J. Sequeira, and S. Mavromatis, “Shallow-water Image Enhancement Using Relative Global Histogram Stretching Based on Adaptive Parameter Acquisition,” in 24th International Conference on Multimedia Modeling – MMM2018, Bangkok, Thailand, 2018.
    [Bibtex]
    @inproceedings{mavromatis2018-MMM,
    TITLE = {{Shallow-water Image Enhancement Using Relative Global Histogram Stretching Based on Adaptive Parameter Acquisition}},
    AUTHOR = {Huang, Dongmei and Wang, Yan and Song, Wei and Sequeira, Jean and Mavromatis, S{\'e}bastien},
    URL = {https://hal-amu.archives-ouvertes.fr/hal-01632263},
    BOOKTITLE = {{24th International Conference on Multimedia Modeling - MMM2018}},
    ADDRESS = {Bangkok, Thailand},
    YEAR = {2018},
    MONTH = Feb,
    doi = {10.1007/978-3-319-73603-7_37},
    HAL_ID = {hal-01632263},
    HAL_VERSION = {v1},
    }
  • P. Zoppitelli, S. Mavromatis, and J. Sequeira, “Ellipse Detection in Very Noisy Environment,” in WSCG, 2017.
    [Bibtex]
    @inproceedings{mavromatis2017-WSCG,
    title = {{Ellipse Detection in Very Noisy Environment}},
    author = {Zoppitelli, Pierre and Mavromatis, S{\'e}bastien and Sequeira, Jean},
    url = {hhttp://wscg.zcu.cz/wscg2017/poster/I47.html},
    booktitle = {{WSCG}},
    year = {2017},
    month = { Mai },
    x-audience = { international },
    x-city = { Plzen },
    x-conferencestartdate = { 2017-05-29 },
    x-country = { PL },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { fr },
    x-popularlevel = NO
    }
  • Z. Jiahui, S. Mavromatis, Q. Meng, J. Sequeira, and Z. Ying, “Using mathematical morphology on lidar data to extract information from urban vegetation,” in IGARSS, 2016.
    [Bibtex]
    @inproceedings{mavromatis2016-IGARSS,
    title = {{Using mathematical morphology on lidar data to extract information from urban vegetation}},
    author = {Jiahui, Zhang and Mavromatis, S{\'e}bastien and Meng, Qingyan and Sequeira, Jean and Ying, Zhang},
    url = {https://hal-amu.archives-ouvertes.fr/hal-01389854},
    booktitle = {{IGARSS}},
    year = {2016},
    month = { Jul },
    x-audience = { international },
    x-city = { Beijing },
    x-conferencestartdate = { 2016-06-10 },
    x-country = { CH },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { fr },
    x-popularlevel = NO
    }
  • M. Daniel, C. Guyot, S. Mavromatis, and A. Polette, “Réalité virtuelle et manipulation de surfaces b-splines,” in Journées du gtmg, Strasbourg, 2012, p. 121–126.
    [Bibtex]
    @inproceedings {mavromatis2012RV,
    title = { R{\'e}alit{\'e} virtuelle et manipulation de surfaces B-splines },
    audience = { nationale },
    author = { Daniel, Marc and Guyot, C{\'e}dric and Mavromatis, S{\'e}bastien' and Polette, Arnaud },
    booktitle = { Journ{\'e}es du GTMG },
    pages = { 121--126 },
    address = { Strasbourg },
    month = { march },
    year = { 2012 },
    x-audience = { international },
    x-city = { Strasbourg },
    x-conferencestartdate = { 2012-03-21 },
    x-country = { FR },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { fr },
    x-popularlevel = NO
    }
  • [DOI] S. Mavromatis, C. Palmann, and J. Sequeira, “Characterization of similar areas of two 2d point clouds,” in Advances in visual computing, 2012, p. 509–516.
    [Bibtex]
    @inproceedings{mavromatis2012characterization,
    title = { Characterization of Similar Areas of Two 2D Point Clouds },
    author = { Mavromatis, S{\'e}bastien and Palmann, Christophe and Sequeira, Jean },
    booktitle = { Advances in Visual Computing },
    pages = { 509--516 },
    year = { 2012 },
    publisher = { Springer Berlin Heidelberg },
    doi = { 10.1007/978-3-642-33191-6_50 },
    url = { http://dx.doi.org/10.1007/978-3-642-33191-6_50 },
    abstract = { We here present a new approach to characterize similar areas of two 2D point clouds, which is a major issue in Pattern Recognition and Image Analysis. To do so, we define a similarity measure that takes into account several criteria such as invariance by rotation, outlier elimination, and one-dimensional structure enhancement. We use this similarity measure to associate locations from one cloud to the other, to use this result in the frame of a registration process between these two point clouds. Our main contributions are the integration of various one-dimensional structure representations into a unified formalism, and the design of a robust estimator to evaluate the common information related to these structures. Finally, we show how to use this approach to register images of different modalities. },
    x-audience = { international },
    x-city = { Crete },
    x-conferencestartdate = { 2012-07-16 },
    x-country = { GR },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • [DOI] F. Graglia, J. Sequeira, and S. Mavromatis, “Real-time walkthrough rendering – speed improvement of photon mapping algorithm,” in Proceedings of the international conference on computer graphics theory and applications (visigrapp 2012), 2012, p. 291–298.
    [Bibtex]
    @inproceedings{graglia2012real,
    title = { Real-time Walkthrough Rendering - Speed Improvement of Photon Mapping Algorithm },
    author = { Graglia, Florian and Sequeira, Jean and Mavromatis, S{\'e}bastien },
    booktitle = { Proceedings of the International Conference on Computer Graphics Theory and Applications (VISIGRAPP 2012) },
    pages = { 291--298 },
    year = { 2012 },
    doi = { 10.5220/0003817702910294 },
    abstract = { The main purpose of this paper is to discuss the global illumination methods in the context of real-time walkthrough. Our work focuses on an accurate illumination of complex scenes; the intensity of the lights can also be interactively modified. This feature is particularly relevant within the context of a production pipeline: After the 3D modeling, photorealistic walkthrough is often used to detect inappropriate reflections or to measure illumination rates. The known methods that usually work in real-time do not simulate all light paths for large scenes. However, some methods provide a full global illumination with a computation time close to a few seconds. This paper shows how this calculation time can be reduced to approach real-time animation thanks to a specific method derived from the photon mapping. },
    x-audience = { international },
    x-city = { Rome },
    x-conferencestartdate = { 2012-02-24 },
    x-country = { IT },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • [DOI] C. Palmann, S. Mavromatis, and J. Sequeira, “A new geometric invariant to match regions within remote sensing images of different modalities,” in Spie remote sensing, 2011, p. 818003–818003.
    [Bibtex]
    @inproceedings{palmann2011new,
    title = { A new geometric invariant to match regions within remote sensing images of different modalities },
    author = { Palmann, Christophe and Mavromatis, S{\'e}bastien and Sequeira, Jean },
    booktitle = { SPIE Remote Sensing },
    pages = { 818003--818003 },
    year = { 2011 },
    organization = { International Society for Optics and Photonics },
    doi = { 10.1117/12.898158 },
    abstract = { The use of several images of various modalities has been proved to be useful for solving problems arising in many different applications of remote sensing. The main reason is that each image of a given modality conveys its own part of specific information, which can be integrated into a single model in order to improve our knowledge on a given area. With the large amount of available data, any task of integration must be performed automatically. At the very first stage of an automated integration process, a rather direct problem arises : given a region of interest within a first image, the question is to find out its equivalent within a second image acquired over the same scene but with a different modality. This problem is difficult because the decision to match two regions must rely on the common part of information supported by the two images, even if their modalities are quite different. In this paper, we propose a new method to address this problem. },
    x-audience = { international },
    x-city = { Prague },
    x-conferencestartdate = { 2011-10-26 },
    x-country = { CZ },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • C. Palmann, S. Mavromatis, and J. Sequeira, “Mesure de similarité entre sous-parties de nuages de points 2d,” in Taima’11 ateliers francophones sur le traitment et l’analyse de l’information, méthodes et applications, 2011.
    [Bibtex]
    @inproceedings{palmann2011mesure,
    title = { Mesure de similarit{\'e} entre sous-parties de nuages de points 2D },
    author = { Palmann, Christophe and Mavromatis, S{\'e}bastien and Sequeira, Jean },
    booktitle = { TAIMA'11 Ateliers francophones sur le Traitment et l'analyse de l'information, méthodes et applications },
    year = { 2011 },
    abstract = { Cet article porte sur la caractérisation d'une mesure de similarité entre sous-parties de nuages de points 2D. Cette mesure est définie à partir d'une hypothèse généralement vérifiée sur des nuages de points issus de cas réels: ceux-ci possèdent des groupes de points qui s'organisent en structures linéiques, et qui apparaissent en même temps dans les différents nuages. Après avoir défini des primitives qui permettent une représentation unifiée de ces structures, nous montrons le lien qui existe entre la présence d'une information commune entre sous-nuages et la distribution des relations géométriques entre leurs primitives. Nous donnons alors une mesure de similarité invariante par rotation, ainsi qu'un algorithme permettant de la calculer. },
    x-audience = { international },
    x-city = { Hammamet },
    x-conferencestartdate = { 2011-10-03 },
    x-country = { TN },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { fr },
    x-popularlevel = NO
    }
  • [DOI] C. Palmann, S. Mavromatis, and J. Sequeira, “A new approach for registering remote sensing images from various modalities,” in Spie europe remote sensing, 2009, p. 74770C–74770C.
    [Bibtex]
    @inproceedings{palmann2009new,
    title = { A new approach for registering remote sensing images from various modalities },
    author = { Palmann, Christophe and Mavromatis, S{\'e}bastien and Sequeira, Jean },
    booktitle = { SPIE Europe Remote Sensing },
    pages = { 74770C--74770C },
    year = { 2009 },
    organization = { International Society for Optics and Photonics },
    doi = { 10.1117/12.830248 },
    abstract = { Image registration is a major issue in the field of Remote Sensing because it provides a support for integrating information from two or more images into a model that represents our knowledge on a given application. It may be used for comparing the content of two segmented images captured by the same sensor at different times; but it also may be used for extracting and assembling information from images captured by various sensors corresponding to different modalities (optical, radar,). The registration of images from different modalities is a very difficult problem because data representations are different (e.g. vectors for multispectral images and scalar values for radar ones) but also, and especially, because an important part of the information is different from an image to another (e.g. hyperspectral signature and radar response). And precisely, any registration process is based, explicitly or not, on matching the common information in the two images. The problem we are interested in is to develop a generic approach that enables the registration of two images from different modalities when their spatial representations are related by a rigid transformation. This situation often occurs, and it requires a very robust and accurate registration process to provide the spatial correspondence. First, we show that this registration problem between images from different modalities can be reduced to a matching problem between binary images. There are many approaches to tackle this problem, and we give an overview of these approaches. But we have to take into account the specificity of the context in which we have to solve this problem: we must select those points of both images that are associated with the same information, and not the other ones, in order to process the pairing that will lead to the registration parameters. The approach we propose is a Hough-like method that induces a separation between relevant and non-relevant pairings, the Hough space being a representation of the rigid transformation parameters. In order to characterize the relevant items in each image, we propose a new primitive that provides a local representation of patterns in binary images. We give a complete description of this approach and results concerning various types of images to register. },
    x-audience = { international },
    x-city = { Berlin },
    x-conferencestartdate = { 2009-08-31 },
    x-country = { DE },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { fr },
    x-popularlevel = NO
    }
  • B. Zoudji, H. Ripoll, L. Llucia, S. Mavromatis, and J. Sequeira, “Simulfoot : un outil technologique pour l’analyse et la formation tactique en football,” in Visions prospectives du professionnalisme sportif en algérie, 2009.
    [Bibtex]
    @inproceedings{zoudji2009simulfoot,
    title = { SimulFoot : un outil technologique pour l'analyse et la formation tactique en football },
    author = { Zoudji, Bachir and Ripoll, Hubert and Llucia, Ludovic and Mavromatis, S{\'e}bastien and Sequeira, Jean },
    booktitle = { Visions prospectives du professionnalisme sportif en Alg{\'e}rie },
    year = { 2009 },
    abstract = { Non disponible },
    x-audience = { international },
    x-city = { Alger },
    x-conferencestartdate = { 2009-01-25 },
    x-country = { DZ },
    x-invitedcommunication = YES,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { fr },
    x-popularlevel = NO
    }
  • [DOI] L. Llucia, S. Mavromatis, S. Perrotte, P. Dias, and J. Sequeira, “Camera location and aperture characterization using the transformation between a 2d plane and the image captured by the camera,” in Image analysis and recognition, 2008, p. 385–394.
    [Bibtex]
    @inproceedings{llucia2008camera,
    title = { Camera location and aperture characterization using the transformation between a 2D plane and the image captured by the camera },
    author = { Llucia, Ludovic and Mavromatis, S{\'e}bastien and Perrotte, S{\'e}bastien and Dias, Paulo and Sequeira, Jean },
    booktitle = { Image Analysis and Recognition },
    pages = { 385--394 },
    year = { 2008 },
    doi = { 10.1007/978-3-540-69812-8_38 },
    organization = { Springer Berlin Heidelberg },
    abstract = { This paper uses as starting point the transformation matrix defined in the homogeneous space that associates the points of a 2D plane (that represents the model) with those of another 2D space (the image one), this transformation characterizing the camera capture process. This transformation (an homography from 2D to 2D) is coming from previous work and is used within the scope of the SimulFoot project. The final objective is to reconstruct a 3D model from TV soccer scenes, making it important to characterize the transformation between a 2D plane (the soccer field) and the camera image. We suppose the transformation (from image to field) is a conic projection whose center is S and projection plane is P in the model 3D space. We formulate two additional hypotheses related to the reference system of P: its origin is the orthogonal projection of S on P, and its first basis vector is parallel to the horizontal plane xOy. In fact, these conditions are often verified in soccer scenes since the camera is fixes on a tripod. In this communication, we give the camera location and aperture expressions on the only basis of the transformation matrix values. },
    x-audience = { international },
    x-city = { Povoa de Varzim },
    x-conferencestartdate = { 2008-06-25 },
    x-country = { PT },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { fr },
    x-popularlevel = NO
    }
  • C. Palmann, S. Mavromatis, and J. Sequeira, “Sar image registration using a new approach based on the generalized hough transform,” in Isprs 2008, 2008.
    [Bibtex]
    @inproceedings{palmann2008sar,
    title = { SAR image registration using a new approach based on the generalized hough transform },
    author = { Palmann, Christophe and Mavromatis, S{\'e}bastien and Sequeira, Jean },
    booktitle = { ISPRS 2008 },
    year = { 2008 },
    issn = { 1682-1750 },
    abstract = { Radar Imaging using SAR systems provides specific information that is very useful in the frame of “Digital Earth ” applications (i.e. flood supervision, forestry or agriculture watch,). The main interest of such active systems is their capability to gather relevant data whatever the weather and the illumination conditions may be (cloudy, misty, during the night,). In addition, these systems give a useful “distance map ” thanks to the wave coherence. Most applications require a follow-up of the situation during weeks or months. Such a follow-up can only be performed if we are able to register images captured at different times. This registration problem is a very classical one and has been widely studied in Remote Sensing, but the proposed solutions are often dedicated to specific contexts (sensors, type of scenes, known relevant elements).Many algorithms have been proposed to register SAR images, and we give, in this paper, a global overview of these methods depending on the chosen approach. They may use filtering or not prior to registration, and they may use landmarks or not; but, in all cases, there will be to take into account the speckle that reduces the efficiency of classical methods for extracting features (e.g. landmarks,) to be paired in both images. During the last years (since 2000), a new set of methods, related to the Hough Transform concept, have been proposed: the algorithm we introduce in this communication can be considered as being in this class of approaches. },
    x-audience = { international },
    x-city = { Beijing },
    x-conferencestartdate = { 2008-07-03 },
    x-country = { CN },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { fr },
    x-popularlevel = NO
    }
  • H. Ripoll, L. Llucia, S. Mavromatis, B. Zoudji, and J. Sequeira, “Simulfoot entraînement, un outil de simulation pour les entraîneurs et les joueurs,” in 3ème colloque international football & recherches, 2008.
    [Bibtex]
    @inproceedings{ripoll2008simulfoot,
    title = { SimulFoot entraînement, un outil de simulation pour les entraîneurs et les joueurs },
    author = { Ripoll, Hubert and Llucia, Ludovic and Mavromatis, S{\'e}bastien and Zoudji, Bachir and Sequeira, Jean },
    booktitle = { 3{\`e}me Colloque International Football \& Recherches },
    year = { 2008 },
    abstract = { Non disponible },
    x-audience = { international },
    x-city = { Valencienne },
    x-conferencestartdate = { 2008-05-19 },
    x-country = { FR },
    x-invitedcommunication = YES,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { fr },
    x-popularlevel = NO
    }
  • [DOI] S. Mavromatis, P. Dias, and J. Sequeira, “3d reconstruction of soccer sequences using non-calibrated video cameras,” in Image analysis and recognition, 2007, p. 1254–1264.
    [Bibtex]
    @inproceedings{mavromatis20073d,
    title = { 3D reconstruction of soccer sequences using non-calibrated video cameras },
    author = { Mavromatis, S{\'e}bastien and Dias, Paulo and Sequeira, Jean },
    booktitle = { Image Analysis and Recognition },
    pages = { 1254--1264 },
    year = { 2007 },
    organization = { Springer Berlin Heidelberg },
    doi = { 10.1007/978-3-540-74260-9_111 },
    abstract = { We present a global approach that enables the production of 3D soccer sequences from non-calibrated video cameras. Our system can produce a 3D animated model of the scene from a single non-calibrated moving camera (a TV sequence for example). The results presented here are very encouraging even with a single camera approach and will probably improve with the future introduction of multiple images that will help resolving occlusion issues and integrating into a single model information coming from various locations on the field. The key point of our approach is that it doesn’t need any camera calibration and it still works when the camera parameters vary along the process. Details on the registration and tracking processes are given as well as the description of the “Virtual Reality” system used for displaying the resulting animated model. },
    x-audience = { international },
    x-city = { Montreal },
    x-conferencestartdate = { 2007-08-22 },
    x-country = { CA },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • [DOI] A. Le Troter, S. Mavromatis, J. Boï, and J. Sequeira, “Automatic landmark detection and validation in soccer video sequences,” in Computer vision and graphics, 2007, p. 774–779.
    [Bibtex]
    @inproceedings{le2006automatic,
    title = { Automatic Landmark Detection and Validation in Soccer Video Sequences },
    author = { Le Troter, Arnaud and Mavromatis, S{\'e}bastien and Boï, Jean-Marc and Sequeira, Jean },
    booktitle = { Computer Vision and Graphics },
    pages = { 774--779 },
    year = { 2007 },
    organization = { Springer Netherlands },
    doi = { 10.1007/1-4020-4179-9_112 },
    abstract = { Landmarks are specific points that can be identified to provide efficient matching processes. Many works have been developed for detecting automatically such landmarks in images: our purpose is not to propose a new approach for such a detection but to validate the detected landmarks in a given context that is the 2D to 3D registration of soccer video sequences. The originality of our approach is that it globally takes into consideration the color and the spatial coherence of the field to provide such a validation. This process is a part of the SIMULFOOT project whose objective is the 3D reconstruction of the scene (players, referees, ball) and its animation as a support for cognitive studies and strategy analysis. },
    x-audience = { international },
    x-city = { Warsaw },
    x-conferencestartdate = { 2007-09-01 },
    x-country = { PL },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • A. Le Troter, S. Mavromatis, J. Boï, and J. Sequeira, “Segmentation d’images en plages de couleurs dominantes,” in Taima’05 ateliers francophones sur le traitment et l’analyse de l’information, méthodes et applications, 2005.
    [Bibtex]
    @inproceedings{le2005segmentation,
    title = { Segmentation d’images en plages de couleurs dominantes },
    author = { Le Troter, Arnaud and Mavromatis, S{\'e}bastien and Boï, Jean-Marc and Sequeira, Jean },
    booktitle = { TAIMA'05 Ateliers francophones sur le Traitment et l'analyse de l'information, méthodes et applications },
    year = { 2005 },
    abstract = { Non disponible },
    x-audience = { international },
    x-city = { Hammamet },
    x-conferencestartdate = { 2005-09-26 },
    x-country = { TN },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { fr },
    x-popularlevel = NO
    }
  • [DOI] A. Le Troter, S. Mavromatis, and J. Sequeira, “Soccer field detection in video images using color and spatial coherence,” in Image analysis and recognition, 2004, p. 265–272.
    [Bibtex]
    @inproceedings{le2004soccer,
    title = { Soccer field detection in video images using color and spatial coherence },
    author = { Le Troter, Arnaud and Mavromatis, S{\'e}bastien and Sequeira, Jean },
    booktitle = { Image Analysis and Recognition },
    pages = { 265--272 },
    year = { 2004 },
    organization = { Springer Berlin Heidelberg },
    doi = { 10.1007/978-3-540-30126-4_33 },
    abstract = { We present an original approach based on the joint use of color and spatial coherence to automatically detect the soccer field in video sequences. We assume that the corresponding area is significant enough for that. This assumption is verified when the camera is oriented toward the field and does not focus on a given element of the scene such as a player or the ball. We do not have any assumption on the color of the field. We use this approach to automatically validate the image area in which the relevant scene elements are. This is a part of the SIMULFOOT project whose objective is the 3D reconstruction of the scene (players, referees, ball) and its animation as a support for cognitive studies and strategy analysis. },
    x-audience = { international },
    x-city = { Porto },
    x-conferencestartdate = { 2004-09-29 },
    x-country = { PT },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • A. Le Troter, S. Mavromatis, and J. Sequeira, “Automatic selection of a region of interest in 3d scene images: application to video captured scenes,” in Advanced concepts for intelligent vision systems (acivs), 2004.
    [Bibtex]
    @inproceedings{le2004automatic,
    title = { Automatic selection of a region of interest in 3D scene images: application to video captured scenes },
    author = { Le Troter, Arnaud and Mavromatis, S{\'e}bastien and Sequeira, Jean },
    booktitle = { Advanced Concepts for Intelligent Vision Systems (ACIVS) },
    year = { 2004 },
    abstract = { This paper introduces an original approach to automatically select a Region of Interest in an image that represents a 3D scene. We assume that the Region of Interest background is significant enough to be characterized by its color and its spatial coherence. We use these two features to provide such a selection that is the first step of a 2D to 3D registration process for analyzing video captured sport scenes. The whole project includes the 3D reconstruction of the scene (players, referees, ball) and its animation as a support for cognitive studies and strategy analysis. },
    x-audience = { international },
    x-city = { Brussels },
    x-conferencestartdate = { 2004-08-31 },
    x-country = { BE },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • H. Ripoll, A. Le Troter, J. Baratgin, S. Mavromatis, M. Faissolle, F. Zmilsony, G. Poplu, J. Petit, and J. Sequeira, “The interest of simulation for research and training in sport: the example of football,” in Proceedings of the third international sport sciences days, the analysis of elite performance in its contextual environment (insep), 2004.
    [Bibtex]
    @inproceedings{ripoll2004interest,
    title={The interest of simulation for research and training in sport: the example of football},
    author={Ripoll, Hubert and Le Troter, Arnaud and Baratgin, Jean and Mavromatis, S{\'e}bastien and Faissolle, M and Zmilsony, F and Poplu, G{\'e}rald and Petit, JP and Sequeira, Jean},
    booktitle={Proceedings of the Third International Sport Sciences Days, The analysis of elite performance in its contextual environment (INSEP)},
    year={2004},
    abstract = { Non disponible },
    x-audience = { international },
    x-city = { Paris },
    x-conferencestartdate = { 2004-09-01 },
    x-country = { FR },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • H. Ripoll, A. Le Troter, J. Baratgin, S. Mavromatis, M. Faissolle, F. Zmilsony, G. Poplu, J. Petit, and J. Sequeira, “Un simulateur pour l’entra\^\inement en football,” in Journées internationales des sciences du sport (insep), 2004.
    [Bibtex]
    @inproceedings{ripoll2004simulateur,
    title={Un simulateur pour l’entra{\^\i}nement en football},
    author={Ripoll, Hubert and Le Troter, Arnaud and Baratgin, Jean and Mavromatis, S{\'e}bastien and Faissolle, M and Zmilsony, F and Poplu, G{\'e}rald and Petit, Jean-Philippe and Sequeira, Jean},
    booktitle={Journ{\'e}es Internationales des Sciences du Sport (INSEP)},
    year={2004},
    abstract = { Non disponible },
    x-audience = { international },
    x-city = { Paris },
    x-conferencestartdate = { 2004-09-01 },
    x-country = { FR },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { fr },
    x-popularlevel = NO
    }
  • S. Mavromatis, J. Baratgin, and J. Sequeira, “Analyzing team sport strategies by means of graphical simulation,” in Icisp 2003, june 2003, agadir, morroco, 2003.
    [Bibtex]
    @inproceedings{mavromatis2003analyzing,
    title={Analyzing team sport strategies by means of graphical simulation},
    author={Mavromatis, S{\'e}bastien and Baratgin, Jean and Sequeira, Jean},
    booktitle={ICISP 2003, June 2003, Agadir, Morroco},
    year={2003},
    abstract = { Non disponible },
    x-audience = { international },
    x-city = { Agadir },
    x-conferencestartdate = { 2003-06-25 },
    x-country = { MA },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • S. Mavromatis and J. Boï, “Texture analysis and scientific visualization,” in Electronic imaging 2003, 2003, p. 115–124.
    [Bibtex]
    @inproceedings{mavromatis2003texture,
    title={Texture analysis and scientific visualization},
    author={Mavromatis, S{\'e}bastien and Boï, Jean-Marc},
    booktitle={Electronic Imaging 2003},
    pages={115--124},
    year={2003},
    abstract = { In this paper, we propose a new formalism that enables to take into account image textural features in a very robust and selective way. This approach also permits to visualize these features so experts can efficiently supervise an image segmentation process based on texture analysis. The texture concept has been studied through different approaches. One of them is based on the notion of ordered local extrema and is very promising. Unfortunately, this approach does not take in charge texture directionality; and the mathematical morphology formalism, on which it is based, does not enable extensions to this feature. This led us to design a new formalism for texture representation which is able to include directionality features. It produces a representation of texture relevant features in the form of a surface z = f (x,y ). The visualization of this surface gives experts sufficient information to discriminate different textures. },
    x-audience = { international },
    x-city = { Santa Clara },
    x-conferencestartdate = { 2003-01-20 },
    x-country = { US },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • S. Mavromatis, J. Baratgin, and J. Sequeira, “Reconstruction and simulation of soccer sequences,” in Mirage, 2003.
    [Bibtex]
    @inproceedings{mavromatis2003reconstruction,
    title={Reconstruction and simulation of soccer sequences},
    author={Mavromatis, S{\'e}bastien and Baratgin, Jean and Sequeira, Jean},
    booktitle={MIRAGE},
    year={2003},
    abstract = { Non disponible },
    x-audience = { international },
    x-city = { Paris },
    x-conferencestartdate = { 2003-05-01 },
    x-country = { FR },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • H. Ripoll, C. Aubert, and S. Mavromatis, “Mechanisms involved in the change of point of view into a 3d-image simulation in sport,” in Xith europeen congress of sport psychology, 2003.
    [Bibtex]
    @inproceedings{ripoll2003mechanisms,
    title={Mechanisms involved in the change of point of view into a 3D-image simulation in sport},
    author={Ripoll, Hubert and Aubert, Christophe and Mavromatis, S{\'e}bastien},
    booktitle={Xith Europeen Congress of Sport Psychology},
    year={2003},
    abstract = { Non disponible },
    x-audience = { international },
    x-city = { Copenhagen },
    x-conferencestartdate = { 2003-07-22 },
    x-country = { DK },
    x-invitedcommunication = NO,
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    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }
  • S. Mavromatis, J. Boï, and J. Sequeira, “Texture analysis using directional local extrema,” in International conference on computer vision and graphics (iccvg), 2002.
    [Bibtex]
    @inproceedings{mavromatis2002texture,
    title={Texture analysis using directional local extrema},
    author={Mavromatis, S{\'e}bastien and Boï, Jean-Marc and Sequeira, Jean},
    booktitle={International Conference on Computer Vision and Graphics (ICCVG)},
    year={2002},
    abstract = { Non disponible },
    x-audience = { international },
    x-city = { Zakopane },
    x-conferencestartdate = { 2002-10-02 },
    x-country = { PL },
    x-invitedcommunication = NO,
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    x-peerreviewing = Yes,
    x-language = { en },
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    }
  • S. Mavromatis, J. Boï, R. Bulot, and J. Sequeira, “Toward the characterization of directional texture classes,” in Proceedings of the 12th portuguese conference on pattern recognition, 2002.
    [Bibtex]
    @inproceedings{mavromatis2002toward,
    title={Toward the characterization of directional texture classes},
    author={Mavromatis, S{\'e}bastien and Boï, Jean-Marc and Bulot, R{\'e}my and Sequeira, Jean},
    booktitle={Proceedings of the 12th Portuguese Conference on Pattern Recognition},
    year={2002},
    abstract = { We propose a new and efficient characterization of directional textures and we show that this approach can be extended to directional texture classes. A texture class is defined as the association of a basic texture with a set of operators that can modify it. This definition enables the development of powerful tools for image segmentation when the relevant information within regions is made of a "slowly moving directional texture". },
    x-audience = { international },
    x-city = { Aveiro },
    x-conferencestartdate = { 2002-06-27 },
    x-country = { PT },
    x-invitedcommunication = NO,
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    x-popularlevel = NO
    }
  • S. Mavromatis, J. Boï, and J. Sequeira, “Tissue differentiation by using texture analysis,” in Conference on biomedical engineering (bioeng), 2001.
    [Bibtex]
    @inproceedings{mavromatis2001tissue,
    title={Tissue differentiation by using texture analysis},
    author={Mavromatis, S{\'e}bastien and Boï, Jean-Marc and Sequeira, Jean},
    booktitle={Conference on Biomedical Engineering (BIOENG)},
    year={2001},
    abstract = { Non disponible },
    x-audience = { international },
    x-city = { Istanbul },
    x-conferencestartdate = { 2001-10-25 },
    x-country = { TR },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
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    }
  • [DOI] S. Mavromatis, J. Boï, and J. Sequeira, “Medical image segmentation using texture directional features,” in Engineering in medicine and biology society, 2001. proceedings of the 23rd annual international conference of the ieee, 2001, p. 2673–2676.
    [Bibtex]
    @inproceedings{mavromatis2001medical,
    title={Medical image segmentation using texture directional features},
    author={Mavromatis, S{\'e}bastien and Boï, Jean-Marc and Sequeira, Jean},
    booktitle={Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE},
    volume={3},
    pages={2673--2676},
    year={2001},
    organization={IEEE},
    doi = { 10.1109/IEMBS.2001.1017333 },
    abstract = { Medical image segmentation can often be performed through tissue texture analysis. One of the most recent and interesting ideas to do that is to take into account the distribution of local maximum orders. We have followed up this idea by using directional maximums and we have applied it to tissue differentiation. Two problems are emerging now: one is the identification of a given texture (labeling) and another one is the characterization of the different areas within images (segmentation). In this paper, we present our new approach for texture representation and analysis, and we point out the advances and problems involved in the image segmentation process. },
    x-audience = { international },
    x-city = { Istanbul },
    x-conferencestartdate = { 2001-10-25 },
    x-country = { TR },
    x-invitedcommunication = NO,
    x-proceedings = YES,
    x-peerreviewing = Yes,
    x-language = { en },
    x-popularlevel = NO
    }

Thèse

  • [PDF] S. Mavromatis, “Analyse de texture et visualisation scientifique,” thesis PhD Thesis, 2001-12-11.
    [Bibtex]
    @phdthesis{mavromatis2001analyse,
    title = { Analyse de texture et visualisation scientifique },
    author = { Mavromatis, S{\'e}bastien },
    year = { 2001-12-11 },
    school = { Universit{\'e} de la M{\'e}diterran{\'e}e },
    type = { thesis },
    pdf = { http://www.sudoc.abes.fr/xslt/DB=2.1//SRCH?IKT=12&TRM=126428433 },
    abstract = { La caract{\'e}risation des propri{\'e}t{\'e}s texturelles d'une image telle qu'elle a {\'e}t{\'e} propos{\'e}e dans ce travail pr{\'e}sente l'avantage de permettre {\`a} un expert d'interagir efficacement avec le processus de segmentation. Cette ouverture est importante car la segmentation d'une image d{\'e}pend largement de l'application dans laquelle elle s'int{\`e}gre, et il est donc indispensable que l'expert puisse conserver un contr{\^o}le sur celle-ci. Ceci a apport{\'e} des solutions, parfois classiques, {\`a} tous les probl{\`e}mes pos{\'e}s dans ce cadre. Cela a permis de montrer la faisabilit{\'e} de cette approche, en m{\^e}me temps que de souligner l'int{\'e}r{\^e}t qu’elle pr{\'e}sente. },
    x-director = { Boi, Jean-Marc },
    x-keywords_fr = { texture, visualisation },
    x-keywords_en = { texture, visualization },
    x-abstract_fr = { La caract{\'e}risation des propri{\'e}t{\'e}s texturelles d'une image telle qu'elle a {\'e}t{\'e} propos{\'e}e dans ce travail pr{\'e}sente l'avantage de permettre {\`a} un expert d'interagir efficacement avec le processus de segmentation. Cette ouverture est importante car la segmentation d'une image d{\'e}pend largement de l'application dans laquelle elle s'int{\`e}gre, et il est donc indispensable que l'expert puisse conserver un contr{\^o}le sur celle-ci. Ceci a apport{\'e} des solutions, parfois classiques, {\`a} tous les probl{\`e}mes pos{\'e}s dans ce cadre. Cela a permis de montrer la faisabilit{\'e} de cette approche, en m{\^e}me temps que de souligner l'int{\'e}r{\^e}t qu’elle pr{\'e}sente. },
    x-abstract_en = { La caract{\'e}risation des propri{\'e}t{\'e}s texturelles d'une image telle qu'elle a {\'e}t{\'e} propos{\'e}e dans ce travail pr{\'e}sente l'avantage de permettre {\`a} un expert d'interagir efficacement avec le processus de segmentation. Cette ouverture est importante car la segmentation d'une image d{\'e}pend largement de l'application dans laquelle elle s'int{\`e}gre, et il est donc indispensable que l'expert puisse conserver un contr{\^o}le sur celle-ci. Ceci a apport{\'e} des solutions, parfois classiques, {\`a} tous les probl{\`e}mes pos{\'e}s dans ce cadre. Cela a permis de montrer la faisabilit{\'e} de cette approche, en m{\^e}me temps que de souligner l'int{\'e}r{\^e}t qu’elle pr{\'e}sente. },
    x-title_fr = { Analyse de texture et visualisation scientifique },
    x-title_en = { Texture analysis and scientific visualisation },
    x-audience = { international },
    x-peerreviewing = Yes,
    x-language = { fr },
    x-filesource = { author },
    x-popularlevel = NO
    }