By Topic

Robust multipose face detection in images

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
$31 $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

3 Author(s)
Rong Xiao ; Microsoft Res. Asia, Beijing, China ; Ming-Jing Li ; Hong-Jiang Zhang

Automatic human face detection from images in surveillance and biometric applications is a challenging task due to variations in image background, view, illumination, articulation, and facial expression. We propose a novel three-step face detection approach to addressing this problem. The approach adopts a simple-to-complex strategy. First, a linear-filtering algorithm is applied to enhance detection performance by removing most nonface-like candidates rapidly. Second, a boosting chain algorithm is adopted to combine the boosting classifiers into a hierarchical "chain" structure. By utilizing the inter-layer discriminative information, this algorithm reveals a higher efficiency than traditional approaches. Last, a postfiltering algorithm, consisting of image preprocessing; support vector machine-filter and color-filter, is applied to refine the final prediction. As only a few candidate windows remain in the final stage, this algorithm greatly improves detection accuracy with small computation cost. Compared with conventional approaches, this three-step approach is shown to be more effective and capable of handling more pose variations. Moreover, together with a two-level hierarchy in-plane pose estimator, a rapid multiview face detector is built. Experimental results demonstrate a significant performance improvement for the proposed approach over others.

Published in:

Circuits and Systems for Video Technology, IEEE Transactions on  (Volume:14 ,  Issue: 1 )