@inproceedings{allili_adaptive_2007,

title = {Adaptive appearance model for object contour tracking in videos},

author = {M. S. Allili and D. Ziou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-34548723968&doi=10.1109%2fCRV.2007.9&partnerID=40&md5=c10008163f7f45f743ef0dcb13444c72},

doi = {10.1109/CRV.2007.9},

isbn = {0769527868 (ISBN); 978-076952786-4 (ISBN)},

year  = {2007},

date = {2007-01-01},

booktitle = {Proceedings - Fourth Canadian Conference on Computer and Robot Vision, CRV 2007},

pages = {510–517},

address = {Montreal, QC},

abstract = {In this paper, we propose a novel object tracking algorithm in video sequences. The formulation of the object tracking is based on variational calculus, where an adaptive parametric mixture model is used for object features representation. The tracking is based on matching the object mixture models between successive frames of the sequence by using active contours while adapting the mixture model to varying object appearance changes due to illumination conditions and camera geometry. The implementation of the method is based on level set active contours which allow for automatic topology changes and stable numerical schemes. We validate our approach on examples of object tracking performed on real video sequences. © 2007 IEEE.},

note = {Journal Abbreviation: Proc. Fourth Can. Conf. Comput. Robot Vis.},

keywords = {Adaptive parametric mixture models, Adaptive systems, Boundary, Color, Geometry, Image communication systems, Level sets, Level-sets, Mathematical models, Mixture of pdfs, Object mixture modelss, Pattern matching, Shape, Target tracking, Texture, Tracking, Variational techniques, Video sequences, Video signal processing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{allili_object_2006,

title = {Object contour tracking in videos by matching finite mixture models},

author = {M. S. Allili and D. Ziou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-34547433254&doi=10.1109%2fAVSS.2006.83&partnerID=40&md5=aeed9598e325243f03c379766e7ac32c},

doi = {10.1109/AVSS.2006.83},

isbn = {0-7695-2688-8 978-0-7695-2688-1},

year  = {2006},

date = {2006-01-01},

booktitle = {Proceedings - IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006},

address = {Sydney, NSW},

abstract = {In this paper, we propose a novel object tracking algorithm in video sequences. The method is based on object mixture matching between successive frames of the sequence by using active contours. Only the segmentation of the objects in the first frame is required for initialization. The evolution of the object contour on a current frame aims to find the maximum fidelity of the mixture likelihood for the same object between successive frames while having the best fit of the mixture parameters to the homogenous parts of the objects. To permit for a precise and robust tracking, region, boundary and shape information are coupled in the model. The method permits for tracking multi-class objects on cluttered and non-static backgrounds. We validate our approach on examples of tracking performed on real video sequences. © 2006 IEEE.},

keywords = {Boundary conditions, Color image processing, Contour measurement, Finite mixture models, Image analysis, Level sets, Object contour tracking, Pattern matching, Shape information, Video signal processing},

pubstate = {published},

tppubtype = {inproceedings}

}