Evaluation framework on translation-invariant representation for cumulative foot pressure image

Ground reaction force can be used to distinguish different human gait like limb movement. Cumulative foot pressure image is a 2-D data that recorded the spatial and temporal change of ground reaction force during one gait cycle. However, when putting it into practice as a new biometric for gait recognition, it suffers from the problem of large translation variation within class caused by wearing different shoes and walking in different speed. In this paper, an evaluation framework is proposed to address the problem. The framework consists of a database containing cumulative foot pressure images and a well designed benchmark. The data are collected from 118 subjects. A locality-constrained sparse coding scheme is developed to be compared with the benchmark PCA approach. Experimental results show the potential of evaluation framework for evaluating the translation-invariant power of image representation algorithms.