@conference {12585,
	title = {Human Identification using Gait and Face},
	booktitle = {Computer Vision and Pattern Recognition, 2007. CVPR {\textquoteright}07. IEEE Conference on},
	year = {2007},
	month = {2007/06//},
	pages = {1 - 2},
	abstract = {In general the visual-hull approach for performing integrated face and gait recognition requires at least two cameras. In this paper we present experimental results for fusion of face and gait for the single camera case. We considered the NIST database which contains outdoor face and gait data for 30 subjects. In the NIST database, subjects walk along an inverted Sigma pattern. In (A. Kale, et al., 2003), we presented a view-invariant gait recognition algorithm for the single camera case along with some experimental evaluations. In this chapter we present the results of our view-invariant gait recognition algorithm in (A. Kale, et al., 2003) on the NIST database. The algorithm is based on the planar approximation of the person which is valid when the person walks far away from the camera. In (S. Zhou et al., 2003), an algorithm for probabilistic recognition of human faces from video was proposed and the results were demonstrated on the NIST database. Details of these methods can be found in the respective papers. We give an outline of the fusion strategy here.},
	keywords = {algorithm;visual-hull, analysis;image, approach;cameras;face, approximation;probabilistic, database;camera;face, databases;, fusion;face, fusion;human, fusion;probability;video, Gait, identification;planar, NIST, processing;visual, recognition, recognition;gait, recognition;view-invariant, signal},
	doi = {10.1109/CVPR.2007.383523},
	author = {Chellapa, Rama and Roy-Chowdhury, A.K. and Kale, A.}
}
