Representation of motion activity in hierarchical levels for video indexing and filtering

A method for video indexing and filtering based on motion activity characteristics in hierarchical levels is proposed. To extract motion activity information, an MPEG (MPEG-1/2) video is first adaptively segmented into hierarchical levels with fixed percentage of original video length based on P-frame macroblock motion information. Three motion activity characteristics-motion intensity which represents the degree of change in motion, motion intensity histogram which represents the temporal statistics of motion intensity, and spatial descriptor which represents the spatial attribute of motion, are then computed to represent different levels of video. The descriptors from different levels are used selectively in different steps of video indexing and filtering. Experimental results show the proposed method is fast and effective, and provides a powerful video indexing and filtering tool.