This paper presents a novel method for recognizing human actions from a series of video frames. The paper uses the idea of an RSD (Region Speed Direction) code generation, which is capable of recognizing most of the common activities in spite of the spatiotemporal variability between subjects. Majority of the researches focus on upper body part or make use of hand and leg trajectories. The trajectory-based approach gives less accurate results due to variability of action pattern between subjects. In RSD Code, we give importance to three factors Region, Speed and Direction to detect the action. These three factors together gives better result for recognizing actions. The proposed method is free from occlusion, positional errors and missing information. The results from our algorithm are comparable to the results of the existing human action detection algorithms.
M. Geetha, Anandsankar, B., Nair, L. S., Amrutha, T., and Rajeev, A., “An Improved Human Action Recognition System Using RSD Code Generation”, in Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing (ICONIAAC '14), 2014.