@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_robust_2006,

title = {A robust video object tracking by using active contours},

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

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33845513941&doi=10.1109%2fCVPRW.2006.20&partnerID=40&md5=64ff2be5c45a6c206420bf6eb5589bca},

doi = {10.1109/CVPRW.2006.20},

isbn = {0769526462 (ISBN); 978-076952646-1 (ISBN)},

year  = {2006},

date = {2006-01-01},

booktitle = {2006 Conference on Computer Vision and Pattern Recognition Workshops},

volume = {2006},

pages = {135},

publisher = {IEEE Computer Society},

address = {New York, NY},

abstract = {In this paper, we propose a novel object tracking algorithm in video sequences. The formulation of our tracking model is based on variational calculus, where region and boundary information cooperate for object boundary localization by using active contours. In the approach, only the segmentation of the objects in the first frame is required for initialization. The evolution of the object contours on a current frame aims to find the boundary of the objects by minimizing the Kullback-Leibler distance of the region feature s distribution in the vicinity of the contour to the objects versus the background respectively. We show the effectiveness of the approach on examples of object tracking performed on real video sequences. © 2006 IEEE.},

note = {Journal Abbreviation: Conf. Comput. Vision Pattern Recog. Workshops},

keywords = {Boundary, Boundary localization, Color, Feature distribution, Image processing, Image segmentation, Kullback-Leibler distance, Level sets, Mathematical models, Mixture of pdfs, Object recognition, Object Tracking, Texture, Tracking (position), Variational techniques, Video object tracking},

pubstate = {published},

tppubtype = {inproceedings}

}