Human Motion Recognition with a Convolution Kernel

Abstract— We address the problem of human motion recognition in this paper. The goal of human motion recognition is to recognize the type of motion recorded in a video clip, which consists of a set of temporarily ordered frames. By defining a Mercer kernel between two video clips directly, we propose in this paper a recognition strategy that can incorporate both the information of each individual frame and the temporal ordering between frames. Combining the proposed kernel with the support vector machine, which is one of the most effective classification paradigms, the resulting recognition strategy exhibits excellent performance over real data sets. Indexed Terms— human motion recognition, convolution kernels, support vector machines.

• Type: Conference
• Year: 2006
• Where: ICRA
• Authors: Dongwei Cao, Osama Masoud, Daniel Boley
• Keywords: Human Motion Recognition, ICRA 2006, Recognition Strategy, Robotics, Support Vector Machines