PANORAMIC CAPTURING AND RECOGNITION OF HUMAN ACTIVITY

Xinding Sun, B. S. Manjunath
Dept. of Electrical and Computer Engineering
University of California at Santa Barbara,
Santa Barbara, CA 93106
E-mail: {xdsun, manj}@ece.ucsb.edu

Abstract

This paper presents a unified approach to human activity
capturing and recognition. It targets applications such as a
speaker walking, turning around, sitting and getting up from a
chair in a classroom setting. A panoramic camera capturing
system is designed for video capture. Virtual camera control
outputs the region of interest (ROI) video that covers the
speaker. Given a ROI sequence, the virtual camera control
parameters are used for the recognition of activities like walking,
and the motion parameters of each frame are used for the
recognition of other activities like turning around, sitting down
and getting up etc. For motion parameter based recognition, the
likelihood of the motion parameters is represented using a
multivariate Gaussian model. The temporal change of the
likelihood is characterized using a continuous density hidden
Markov model (HMM). Experimental results show that the
method works well in recognizing the above mentioned human
body activities.