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Two-view methods have been well developed to identify human actions. However, in a case where the corresponding imaged points cannot induce distinguished measures, the performance of the methods deteriorates. For this reason, we propose a new view-invariant measure for human action recognition by enforcing tri-view constraints in this paper. We apply our approach to video synchronization by imposing...
In this paper we propose a robust and efficient approach to localizing and estimating the motion of non-rigid and articulated objects using marginal trajectory spectrum learning. Detecting the motion directly in the Euclidean space is often found difficult to guarantee a smooth and accurate result and might be affected by drifting. These issues, however, can be addressed effectively by formulating...
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