Video indexing by motion activity maps
Motion based video indexing is an important and active research area in content-based video retrieval. It explores the dynamic characteristics of video content and provides techniques for video representation and retrieval. In this paper, a new motion-based approach is proposed, in which the image generated from motion activity is used to index video. The proposed approach firstly computes the accumulation measurement of motion activity on the grids of video frames along the time axis. Then, the computed measurement is quantized into several gray levels and a gray image is generated from all measurements on the grids. The generated image called motion activity map (MAM) reserves the motion information on different spatial locations of video. The intensity of MAM is corresponding to the magnitude of motion activity. All MAMs are organized into a hierarchical tree according to the video structure. Therefore, user can browse video by the MAMs tree. The proposed approach provides a hierarchical, coarse to fine view of video and thus makes interactive video retrieval more simply and intuitively.