Histogram of directional derivative based spatio-temporal descriptor for human action recognition

In this paper, we introduced a novel local spatio-temporal feature descriptor for human action recognition. Our proposed descriptor is based on the Histogram of Directional Derivative (HODD). Histogram of gradient (HOG) has been widely used to generate the descriptor for local features for human action recognition. The distinctiveness of descriptor is essential to match similar action and differentiate different action. However most of the techniques in literature for HOG is based on orientation quantization leading to the reduction of the distinctiveness. Our proposed descriptor describes the local object shape and appearance within cuboid effectively and distinctively.