View-Invariant Action Recognition Using Rank Constraint
Nazim Ashraf, Yuping Shen, Hassan Foroosh · 2010
We propose a new method for view-invariant action recognition based on the rank constraint on the family of planar homographies associated with triplets of body points. We represent action as a sequence of poses and we use the fact that the family of homographies associated with two identical poses would have rank 4 to gauge similarity of the pose between two subjects, observed by different perspective cameras and from different viewpoints. Extensive experimental results show that our method can accurately identify action from video sequences when they are observed from totally different viewpoints with different camera parameters.