Multiresolution target detection and tracking through a parallel coarse-to-fine search approach

A new pyramidic-structure-based approach to moving object detection and tracking from image sequences is proposed. The approach uses a Gaussian low-pass filter to transform each frame in the image sequences into a multiresolution representation, or a pyramidic structure of the frame. At each level of the image pyramid, a correlative matching process is performed throughout a restricted area to detect and localize the moving object. The pyramidic structures of images used in current matching recurrence are formed in the previous recurrences, and the searching area is determined by the recurrence at the upper level. Theoretical analysis and experiment show that the proposed approach has raised the efficiency by 150 times or more as compared with a conventional matching method. Furthermore, the method for mapping the approach into a deliberately designed parallel processor structure named Elementary Pyramid is investigated for the purpose of speeding up the search performance further.<>