Real-time Stereo Face Recognition by Fusing Appearance and Depth Fisherfaces

被引:0
|
作者
Jian-Gang Wang
Eng Thiam Lim
Xiang Chen
Ronda Venkateswarlu
机构
[1] Institute for Infocomm Research,
关键词
face recognition; stereo; fusion; fisherfaces;
D O I
暂无
中图分类号
学科分类号
摘要
Reported 3D face recognition techniques assume the use of active 3D measurement for 3D facial capture. However, active method employ structured illumination (structure projection, phase shift, gray-code demodulation, etc) or laser scanning, which is not desirable in many applications. A major problem of using passive stereo is its lower 3D face resolution and thus no passive method for 3D face recognition has been reported. In this paper, a real-time passive stereo face recognition system is presented. Entire face detection, tracking, pose estimation and face recognition are investigated. We used SRI Stereo engine that outputs sub-pixel disparity automatically. An investigation is carried out in combining 3D and 2D information for face recognition. The straightforward two-stage principal component analysis plus linear discriminant analysis is carried out in appearance and depth face images respectively. A probe face is identified using sum of the weighted appearance and depth linear discriminant distances. We investigate the complete range of linear combinations to reveal the interplay between these two paradigms. The improvement of the face recognition rate using this combination is verified. The recognition rate by the combination is higher than that of either appearance alone or depth alone. We then discuss the implementation of the algorithm on a stereo vision system. A hybrid face and facial features detection/tracking approach is proposed which collects near-frontal views for face recognition. Our face detection/tracking approach automatically initializes without user intervention and can be re-initialized automatically if the tracking of the 3D face pose is lost. The experiments include two parts. Firstly, the performance of the proposed algorithm is verified on XM2VTS database; Secondly, the algorithm is demonstrated on a real-time stereo vision system. It is able to detect, track and recognize a person while walking toward a stereo camera.
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收藏
页码:409 / 423
页数:14
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