Can gait fluctuations improve gait recognition?

Gait recognition performance is often degraded by intra-subject gait fluctuations such as temporal fluctuations due to non-uniform evolution of phase (gait stance) and spatial fluctuations in arm swings or posture within the same phase. Therefore, we first propose a method for gait recognition using a phase-normalized image sequence to overcome the temporal fluctuations. However, it has been noticed that gait fluctuations actually contain some useful individuality (e.g., degree of arm swing fluctuations). Hence, we propose a score-level fusion framework for gait recognition using the gait fluctuation features as well as the phase-normalized image sequence. Experiments with a public gait database of 100 subjects show the effectiveness of the proposed method.