Human Action Recognition Using Histogram of Oriented Gradient of Motion History Image

This paper presents a human action recognition method using histogram of oriented gradient (HOG) of motion history image (MHI). First, the proposed method generates MHI with differential images which are obtained by frame difference of successive frames of a video. The histogram of oriented gradient (HOG) of the MHI is then computed. Finally, support vector machine (SVM) is applied to train an action classifier using the HOG features. We discovered that the new method improves recognition rate significantly. Moreover, our algorithm does not require the generation process of human silhouette, and therefore the performance is also increased. Experimental results are provided to show the promising performance of the proposed method.