Publications

Copyright information: personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the publisher.

Robust infants face tracking using active appearance models: a mixed-state CONDENSATION approach

Publication type	Book chapter
Year of publication	2007
Authors	Luigi Bagnato, Matteo Sorci, Gianluca Antonini, Giuseppe Baruffa, Andrea Maier, Peter Leathwood, and Jean Michel Thiran
Title	Robust infants face tracking using active appearance models: a mixed-state CONDENSATION approach
Journal title	Lecture Notes in Computer Science - Advances in Visual Computing
Volume	4841
Issue
Pages	13–23
Editor
Publisher	Springer
Date	November 2007
Place	Lake Tahoe, NE
ISSN number	0302-9743
ISBN number	978-3-540-76857-9
Key words	tracking, particle filtering, condensation, model switching, active appearance model
Abstract	In this paper a new extension of the CONDENSATION algorithm, with application to infants face tracking, will be introduced. In this work we address the problem of tracking a face and its features in baby video sequences. A mixed state particle filtering scheme is proposed, where the distribution of observations is derived from an active appearance model. The mixed state approach combines several dynamic models in order to account for different occlusion situations. Experiments on real video show that the proposed approach augments the tracker robustness to occlusions while maintaining the computational time competitive.
URL	http://www.springerlink.com/content/r821k2130xm1428r/
DOI	http://dx.doi.org/10.1007/978-3-540-76858-6_2
Other information	Proceedings of Third International Symposium on Visual Computing, 26-28/11/2007
Paper	(portable document format, 1184846 Bytes)