Histogram of DMHI and LBP images to represent human actions

Recently, motion history images are used as a decent spatiotemporal template to represent human action. Each human action has its distinctive profile and a motion sequence that can be suitably represented by a histogram. In this paper a histogram oriented action recognition method is presented. In the proposed method, we use a mixture of histogram information as a feature vector for action representation. Histograms are taken from directional motion history images and their corresponding local binary pattern images which are then added together. We measured the performance of the proposed method along with some variants of it by employing KTH action dataset and found higher accuracies. The presented results also justify the superiority of the proposed method compared to other approaches for action recognition found in literature.