TY - JOUR T1 - Gait-based human identification from a monocular video sequence JF - Handbook on Pattern Recognition and Computer Vision Y1 - 2004 A1 - Kale, A. A1 - Sundaresan, A. A1 - Roy Chowdhury, A.K. A1 - Chellapa, Rama AB - Human gait is a spatio-temporal phenomenon that characterizes the motion char-acteristics of an individual. It is possible to detect and measure gait even in low- resolution video. In this chapter, we discuss algorithms for identifying people by their gait from a monocular video sequence. Human identification using gait, sim- ilar to text-based speaker identification, involves different individuals performing the same task and a template-matching approach is suitable for such problems. In situations where the amount of training data is limited, we demonstrate the utility of a simple width feature for gait recognition. By virtue of their determin- istic nature, template matching methods have limited noise resilience. In order to deal with noise we introduce a systematic approach to gait recognition by building representations for the structural and dynamic components of gait using exemplars and hidden Markov models (HMMs). The above methods assume that an exact side-view of the subject is available in the probe sequence. For the case when the person walks at an arbitrary angle far away from the camera we present a view invariant gait recognition algorithm which is based on synthesizing a side view of a person from an arbitrary monocular view. ER -