Computational approaches for real-time extraction of soft biometrics

Abstract

Soft biometrics, as a prescreening filter, contribute to a much smaller candidate pool and allow the overall query to perform better and faster. In this paper, we focus on the efficiency and effectiveness of several soft biometrics for surveillance applications. We propose a temporal signature in x-t slices. Such a signature has explicitly embedded body articulation and enables direct mensuration. The algorithms determine characteristics for gender, body size, height, cadence, and stride of the subject using a novel gait analysis tool. We have evaluated algorithm performance under various poses, ranges, and illuminations. Preliminary experiments have shown promising results.