Part-based set matching for face recognition in surveillance

Fei Zheng; Guijin Wang; Xinggang Lin

doi:10.1117/12.2035796

19 December 2013 Part-based set matching for face recognition in surveillance

Fei Zheng, Guijin Wang, Xinggang Lin

Proceedings Volume 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology; 904517 (2013) https://doi.org/10.1117/12.2035796
Event: International Conference on Optical Instruments and Technology (OIT2013), 2013, Beijing, China

Abstract

Face recognition in surveillance is a hot topic in computer vision due to the strong demand for public security and remains a challenging task owing to large variations in viewpoint and illumination of cameras. In surveillance, image sets are the most natural form of input by incorporating tracking. Recent advances in set-based matching also show its great potential for exploring the feature space for face recognition by making use of multiple samples of subjects. In this paper, we propose a novel method that exploits the salient features (such as eyes, noses, mouth) in set-based matching. To represent image sets, we adopt the affine hull model, which can general unseen appearances in the form of affine combinations of sample images. In our proposal, a robust part detector is first used to find four salient parts for each face image: two eyes, nose, and mouth. For each part, we construct an affine hull model by using the local binary pattern histograms of multiple samples of the part. We also construct an affine model for the whole face region. Then, we find the closest distance between the corresponding affine hull models to measure the similarity between parts/face regions, and a weighting scheme is introduced to combine the five distances (four parts and the whole face region) to obtain the final distance between two subjects. In the recognition phase, a nearest neighbor classifier is used. Experiments on the public ChokePoint dataset and our dataset demonstrate the superior performance of our method.

Citation Download Citation

Fei Zheng, Guijin Wang, and Xinggang Lin "Part-based set matching for face recognition in surveillance", Proc. SPIE 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 904517 (19 December 2013); https://doi.org/10.1117/12.2035796

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Affine motion model

Cameras

Surveillance

Facial recognition systems

Eye models

Sensors

Mouth

Show All Keywords

Keywords/Phrases

Search In:

Publication Years