Detecting Activities

Ramprasad Polana and Randal C. Nelson
Department of Computer Science
University of Rochester
Rochester, NY 14627

Abstract: The recognition of repetitive movements characteristic of walking people, galloping horses, or flying birds is a routine function of the human visual system. It has been demonstrated that humans can recognize such activity solely on the basis of motion information. We present a novel computational approach for detecting such activities in real image sequences on the basis of the periodic nature of their signatures. The approach suggests a low-level feature based activity recognition mechanism. This contrasts with earlier model-based approaches for recognizing such activities.