
Proceedings Paper
Multiview face detection using multilayer chained structureFormat | Member Price | Non-Member Price |
---|---|---|
$14.40 | $18.00 |
![]() |
GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. | Check Access |
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
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)
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)
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)
© SPIE. Terms of Use
