Classification of MPEG videos based on motion vectors - Zaw Tin Oo (2008)
This dissertation provides a method of classifying MPEG videos based on Motion Vector. We developed a prototype system that can extract the motion vectors embedded in the video so as to identify the region of interest for segmentation and classification purpose. The two classifications are identified as wide angle shot and neighboring shot. We tested various MPEG-1 and MPEG-2 standard videos and classify them as wide angle and neighboring shots. By extracting the accurate motion characteristics of the video, we are able to classify video sequences based on their different characteristics. We developed tools based on camera motion for analyzing and classifying a class of structured videos using the motion information available directly from MPEG compressed videos. By examining readily extractable data from MPEG video bit streams, such as macroblock motion vectors and the number of intra-coded blocks, we illustrate that it is possible to identify high level events such as wide angle and neighboring views.