Motion retrieval using consistency of epipolar geometry

In this paper, we present an efficient method for motion retrieval method based on the consistency of the homographies with the epipolar geometry. We treat the body pose as body point triplets and use the fact that each homography obtained from corresponding body point triplets should be consistent with epipolar geometry to estimate the similarity of two poses. We show that our method is invariant to camera internal parameters and viewpoint. Experiments are performed on the CMU MoCap dataset, and IXMAS dataset testing testing view-invariance, and action recognition. The results demonstrate that our method can accurately identify human action from video sequences when they are observed from totally different viewpoints with different camera parameters.