@inproceedings{allili_effective_2009,

title = {Effective object tracking by matching object and background models using active contours},

author = {M. S. Allili},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77951940408&doi=10.1109%2fICIP.2009.5414279&partnerID=40&md5=6838bb85dbef6c9548684a506df3d2b2},

doi = {10.1109/ICIP.2009.5414279},

isbn = {15224880 (ISSN); 978-142445654-3 (ISBN)},

year  = {2009},

date = {2009-01-01},

booktitle = {Proceedings - International Conference on Image Processing, ICIP},

pages = {873–876},

publisher = {IEEE Computer Society},

address = {Cairo},

abstract = {In this paper, we propose an effective approach for tracking distribution of objects. The approach uses a competition between a tracked objet and background distributions using active contours. Only the segmentation of the object in the first frame is required for initialization. We evolve the object contour by assigning pixels in a fashion that maximizes the likelihood of the object versus the background. This maximization is implemented using an EM-like algorithm, which evolves the object contour exactly to its boundaries, and adapts the parameters of the object and background distributions. ©2009 IEEE.},

note = {Journal Abbreviation: Proc. Int. Conf. Image Process. ICIP},

keywords = {Active contours, Algorithms, Background model, EM algorithm, EM algorithms, Finite mixture models, Image matching, Image processing, Imaging systems, Mathematical models, Object contour, Object Tracking},

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}

}