基于MPEG压缩域的运动对象检测方法

Moving Object Detection From MPEG Compressed Field

为了从MPEG压缩码流中准确的检测和提取运动对象,本文提出了一种时空域的运动对象检测算法。算法主要利用了MPEG码流中的运动矢量信息,首先对运动矢量进行时域平均和向量中值滤波的预处理,减少运动估计秒准确带来的运动矢量与实际对象运动带来的检测误差。然后建立时域上关于搜索块与参考块之间运动矢量夹角的概率模型,对于帧间预测宏块通过聂曼一皮尔迅准则进行运动判决。同时,对于P、B帧内的编码宏块,提出判决算法区分运动的帧内宏块和重现背景。实验证明,本文算法可以获得较为理想的检测效果。

In this paper, a novel temporal-spatial detection method, which was mainly depended on the motion vector information, was proposed for the detection of moving objects from the MPEG compressed field. Firstly, a temporally average filters and a spatially weighted vectors median filters were applied to the motion vector to alleviate the detection error due to the difference between real motion information and the motion vector. For Inter-MB, a temporally statistical modal with regard to vector angle was established and the moving object was detected by using the neyman-pearson criteria. For Intra-MB, a temporal compare was applied for distinguishing the motion MBs from uncovered background MBs. Experiment results show that the considerable detection could be expected.