Feature Fusion of Face and Gait for Human Recognition at a Distance in Video

A new video based recognition method is presented to recognize non-cooperating individuals at a distance in video, who expose side views to the camera. Information from two biometric sources, side face and gait, is utilized and integrated at feature level. For face, a high-resolution side face image is constructed from multiple video frames. For gait, gait energy image (GEI), a spatio-temporal compact representation of gait in video, is used to characterize human walking properties. Face features and gait features are obtained separately using principal component analysis (PCA) and multiple discriminant analysis (MDA) combined method from the high-resolution side face image and gait energy image (GEI), respectively. The system is tested on a database of video sequences corresponding to 46 people. The results showed that the integrated face and gait features carry the most discriminating power compared to any individual biometric

[1]  Bir Bhanu,et al.  Statistical feature fusion for gait-based human recognition , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[2]  Rama Chellappa,et al.  Fusion of gait and face for human identification , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[3]  Xiaoli Zhou,et al.  Human Recognition at a Distance in Video by Integrating Face Profile and Gait , 2005, AVBPA.

[4]  Arun Ross,et al.  Feature level fusion of hand and face biometrics , 2005, SPIE Defense + Commercial Sensing.

[5]  Wu Zhong.  International Trends of Pattern Recognition Research A Brief Introduction to the 18th International Conference on Pattern Recognition , 2006 .

[6]  Chengjun Liu,et al.  A shape- and texture-based enhanced Fisher classifier for face recognition , 2001, IEEE Trans. Image Process..

[7]  Michal Irani,et al.  Motion Analysis for Image Enhancement: Resolution, Occlusion, and Transparency , 1993, J. Vis. Commun. Image Represent..

[8]  Yongsheng Gao,et al.  Feature-level fusion in personal identification , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[9]  J. Little,et al.  Recognizing People by Their Gait: The Shape of Motion , 1998 .

[10]  Bir Bhanu,et al.  Statistical feature fusion for gait-based human recognition , 2004, CVPR 2004.

[11]  Xiaoli Zhou,et al.  Face recognition from face profile using dynamic time warping , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[12]  Trevor Darrell,et al.  On probabilistic combination of face and gait cues for identification , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.