Human action recognition in RGB-D videosusing motion sequence information and deep learning

Earnest Paul Ijjina C. Krishna Mohan
Abstract In this paper, we propose an approach for recognizing human action based on motion sequence information in RGB-D video using deep learning. A new representation that gives emphasis to the key poses associated with each action is presented. The features obtained from motion in RGB and depth video streams are given as input to the convolutional neural network to learn the discriminative features. The efficacy of the proposed approach is demonstrated on MIVIA action, NATOPS gesture, SBU Kinect ...