  In this paper, a macroblock classification method is proposed for various
video processing applications involving motions. Based on the analysis of the
Motion Vector field in the compressed video, we propose to classify Macroblocks
of each video frame into different classes and use this class information to
describe the frame content. We demonstrate that this low-computation-complexity
method can efficiently catch the characteristics of the frame. Based on the
proposed macroblock classification, we further propose algorithms for different
video processing applications, including shot change detection, motion
discontinuity detection, and outlier rejection for global motion estimation.
Experimental results demonstrate that the methods based on the proposed
approach can work effectively on these applications.
