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Motion Flow Analysis using Bi-directional Prediction-Independent Framework in MPEG Compressed Domain  

김낙우 (중앙대학교 첨단영상대학원 영상공학과)
김태용 (중앙대학교 첨단영상대학원 영상공학과)
최종수 (중앙대학교 첨단영상대학원 영상공학과)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.41, no.5, 2004 , pp. 13-22 More about this Journal
Abstract
Because video sequence consists of dynamic objects in nature, the object motion in video is an effective feature in describing the contents of video sequence and motion feature plays an important role in video retrieval. In this paper, we propose a method that converts motion vectors (MVs) to a uniform set on MPEG coded domain, independent of the frame type and the direction of prediction, and utilizes these normalized MVs (N-MVs) as motion descriptor to understand video contents. We describe a frame-type independent representation of the various types of frames presented in an MPEG video in which all frames can be considered equivalently, without full-decoding. In the experiments, we show that the proposed method is better than the conventional one in terms of performance.
Keywords
Motion analysis; Normalized motion vector; Bi-directional prediction-independent framework;
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