Headprint-based human recognition

Abstract

This chapter presents an innovative approach for unobtrusive person identification especially applicable in surveillance applications. New algorithms for (a) separation of hair area from the background in overhead imagery, (b) extraction of novel features that characterize the color and texture of hair, and (c) person identification given these features are presented. In one scenario, only a single training image per subject is assumed to be available. In another scenario, a small set of up to four training images is used per subject. Successful application on both still and video imagery is demonstrated. Although the visual appearance of hair cannot be used as a long-term biometric due to the nonrigid nature of hair, we demonstrate a realistic scenario where the time interval between gallery and probe imagery is short enough to achieve reliable performance. © 2008 Springer London.