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Fast multiframe motion estimation for surveillance videos

We propose a fast multiple reference frames based motion estimation technique for surveillance videos. In the very first reference frame of each motion vector search, successive elimination algorithm is used to find the best motion vector in the search window. For the remaining reference frames, a difference between current and previous reference frames is performed to indentify candidate matching blocks in the current reference frame. Different block matching strategies are proposed to find the optimum motion vector. Experimental evaluation shows that significant reduction in computational complexity can be achieved by applying the proposed strategy.