NDLI: Facial feature tracking and pose estimation in video sequences by factorial coding of the low-dimensional entropy manifolds due to the partial symmetries of faces

Content Provider	IEEE Xplore Digital Library
Author	Mandel, E.D. Penev, P.S.
Copyright Year	2000
Description	Author affiliation: Lab. of Comput. Sci., Rockefeller Univ., New York, NY, USA (Mandel, E.D.)
Abstract	In a number of practical scenarios, such as video conferencing and visual human/computer interaction, objects that belong to a well defined class are segmented, normalized, and encoded, after which they are stored and/or transmitted, and subsequently reconstructed. The Karhunen-Loeve transform (KLT) optimally concentrates the signal power in a relatively small number of uncorrelated coefficients. Nevertheless, it implicitly assumes a multidimensional Gaussian probability model, which is typically not correct. Here we show that, in the context of video sequences of human heads, the segmentation and normalization steps result in partial symmetries which force the KLT coefficients to lie close to low-dimensional manifolds in suitably chosen high-dimensional KLT subspaces. We show how this fact can be used to track the faces robustly, and to estimate their pose. We use vector quantization to discover those manifolds, and to build a factorial code that has a substantially lower dimensionality than KLT.
Starting Page	2345
Ending Page	2348
File Size	592450
Page Count	4
File Format	PDF
ISBN	0780362934
ISSN	15206149
DOI	10.1109/ICASSP.2000.859311
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-06-05
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Facial features Video sequences Karhunen-Loeve transforms Humans Entropy Videoconference Robustness Statistics Parameter estimation Face detection
Content Type	Text
Resource Type	Article

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Facial Feature Tracking And Pose Estimation In Video Sequences By Factorial Coding Of The Low-Dimensional Entropy Manifolds Due To The Partial Symmetries Of Faces (2000)

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