By Topic

Audio-Guided Video-Based Face Recognition

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Xiaoou Tang ; Dept. of Inf. Eng., Chinese Univ. of Hong Kong (CUHK), Hong Kong, China ; Zhifeng Li

In this paper, we develop a new video-to-video face recognition algorithm. The major advantage of the video-based method is that more information is available in a video sequence than in a single image. In order to take advantage of the large amount of information in the video sequence and at the same time overcome the processing speed and data size problems, we develop several new techniques including temporal and spatial frame synchronization, multilevel discriminant subspace analysis, and multiclassifier integration for video sequence processing. An aligned video sequence for each person is first obtained by applying temporal and spatial synchronization, which effectively establishes the face correspondence using both audio and video information; then multilevel discriminant subspace analysis or multiclassifier integration is employed for further analysis based on the synchronized sequence. The method preserves most of the temporal-spatial information contained in a video sequence. Extensive experiments on the XM2VTS database clearly show the superiority of our new algorithms with near-perfect classification results (99.3%) obtained.

Published in:

IEEE Transactions on Circuits and Systems for Video Technology  (Volume:19 ,  Issue: 7 )