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

Publication typeBook chapter
Year of publication2007
AuthorsLuigi Bagnato, Matteo Sorci, Gianluca Antonini, Giuseppe Baruffa, Andrea Maier, Peter Leathwood, and Jean Michel Thiran
TitleRobust infants face tracking using active appearance models: a mixed-state CONDENSATION approach
Journal titleLecture Notes in Computer Science - Advances in Visual Computing
Volume4841
Issue
Pages13–23
Editor
PublisherSpringer
DateNovember 2007
PlaceLake Tahoe, NE
ISSN number0302-9743
ISBN number978-3-540-76857-9
Key wordstracking, particle filtering, condensation, model switching, active appearance model
AbstractIn 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.
URLhttp://www.springerlink.com/content/r821k2130xm1428r/
DOIhttp://dx.doi.org/10.1007/978-3-540-76858-6_2
Other informationProceedings of Third International Symposium on Visual Computing, 26-28/11/2007
Paper (portable document format, 1184846 Bytes)
Last update: 2015-10-12, 16:44:51