Analyzing Human Movements from Silhouettes via Fourier Descriptor

Human movement analysis has recently gained growing interest for computer vision researchers. In this paper, a simple but efficient algorithm using Fourier descriptor to represent spatial-temporal silhouette for human movement analysis is proposed. For each image sequence, motion detection and segmentation methods are used to segment and extract the moving silhouettes of people. Then, Fourier descriptor(FD)is used to describe the moving silhouettes. HMMs and Haudorff distance are applied to the time-varying distance signals described by FD for the activity classification and gait recognition. Experimental results have demonstrated that the proposed algorithm greatly improve the recognition rates.