Time-sliced averaged motion history image for gait recognition

In this paper, we propose a time-sliced averaged motion history image (TAMHI) alongside the histograms of oriented gradients (HOG) to generate gait signatures in a gait recognition problem. Building on the motion history image (MHI), TAMHI divides the gait cycle into several regular time windows to generate the same number of TAMHI composite images. HOG descriptors are then calculated on these composite images to obtain the gait signature. The time-slicing procedure to produce multi-composite images preserve more detailed transient information of gait cycles. Additionally, time-normalization also introduces gait length invariancy into the representation, hence, offering a better recognition rate to slight changes in walking speed.