Fast Moving Object Extraction Algorithm in Image Sequences

A novel and effective approach to global motion estimation and moving object extraction was proposed.Firstly,the translational motion model was used because of the fact that complex motion could be decomposed as a sum of translational components.Then,the edge gray horizontal and vertical projections were used as the block matching feature for the motion vectors estimation in this application.The proposed algorithm reduced the motion estimation computations by calculating the one-dimensional vectors rather than the two-dimensional ones.Once the global motion was robustly estimated,relatively stationary background could be almost completely eliminated through inter-frame difference method.To achieve an accurate object extraction result,the higher-order statistics(HOS) algorithm was used to discriminate backgrounds and moving objects.Experimental results validate that the proposed method is an effective way for global motion estimation and object extraction.