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Proceedings Paper

Multiview face detection using multilayer chained structure
Author(s): Jung-Bae Kim; Haibing Ren; SeongDeok Lee
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Paper Abstract

To capture human pictures with good quality, auto focus, exposure and white-balance on human face areas is very important. This paper presents a novel method to detect multi-view faces fast and accurately. It combines accurate 3- level all-chain structure algorithm and fast skin color algorithm. The 3-level all-chain structure algorithm has 3 levels and all the levels are linked from the top to the bottom. The level 1 rejects the non-face samples for all the views with improved real-boosting method. The level 2 proposes a specially designed cascade structure with 2 sub levels to estimate and verify the view class of face sample from coarse to fine. The level 3 is independent view verifier for each view. Between neighboring levels(or sub levels), the sample classification confidence of previous level would be passed to next level. Inner each level(or sub levels), the classification confidence of previous stage would be the first weak classifier of next stage. It is because the previous classification result contains very useful information for current situation. The fast skin color algorithm could remove the non-skin area with little computation, which makes the system work much faster. The experimental result shows that this method is very efficient and it could correctly detect the multiview human faces in real-time. It can also estimate the face view class at the same time.

Paper Details

Date Published: 19 January 2009
PDF: 8 pages
Proc. SPIE 7252, Intelligent Robots and Computer Vision XXVI: Algorithms and Techniques, 725206 (19 January 2009); doi: 10.1117/12.806127
Show Author Affiliations
Jung-Bae Kim, Samsung Advanced Institute of Technology (Korea, Republic of)
Haibing Ren, Samsung Advanced Institute of Technology (Korea, Republic of)
SeongDeok Lee, Samsung Advanced Institute of Technology (Korea, Republic of)


Published in SPIE Proceedings Vol. 7252:
Intelligent Robots and Computer Vision XXVI: Algorithms and Techniques
David P. Casasent; Ernest L. Hall; Juha Röning, Editor(s)

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