Human action recognition on simple and complex background in video

In this paper, we propose a new method for human action recognition on simple and complex background. There are two approaches: (a) for homogeneous and static background, we propose a combination of HOG3D and HOF to encode the appearance and motion information of human. (b) with realistic video data (including changes of viewpoint, scale, and lighting conditions, partial occlusion of humans and objects, cluttered backgrounds), we exploit the co-occurrence between scene and actions by combining HOG3D and Opponent SIFT to encode action (how) and scene (where) information. The first combination is applied in surveillance videos or videos in which camera placement and parameters are fixed and known. The second one is applied to remained video in which background is not static and cluttered. The experimental results have shown the efficiency and effectiveness of our method.