Search Patterns Switching for Motion Estimation using Rate of Error Descent
Most of the fast motion estimation algorithms based on search-point pattern are only good at handling videos with small motions, for example, block-based gradient descent search, diamond search and hexagonal-based search. An adaptive motion estimation algorithm which can switch between search patterns for different video contents should work better than a single search pattern algorithm. In this paper, a simple classifier based on error descent rate (EDR) is proposed. This classifier uses a very few number of search points to predict whether the global minimum is far away or near the center of the search window. If it is far away, a search pattern which is good at searching large motions is used. Otherwise, a pattern good at searching small motions is applied. The proposed search patterns switching (SPS) algorithm performs well for all kinds of video contents.