在MPEG视频上的语义视频对象分割改进算法

随着MPEG－4，MPEG－7等标准的提出，如何提取语义视频对象已成为当前视频压缩和检索领域共同的研究课题。特别是MPEG－7对视频对象的形状检索提出了具体要求。针对顾创等人的WaterShed算法不能很好处理现有MPEG－1视频数据的缺陷，提出改进算法，从而能够在MPEG视频流中提取到具有光滑轮廓的语义视频对象，算法主要有以下两点改进：提出将类成员数作为分类算法的参数；有压缩域和解码后的图像上先后进行两次分割。实验结果表明，改进算法在鲁棒性和分割结果精度上比原算法有较大的改进，其分割结果可用于轮廓检索和重要视频对象检索。

An Improved Semantic Video Object Segmentation Algorithm for MPEG Video Data

With the advent of MPEG 4 and MPEG 7, the segmentation of SVO (semantic video object) becomes the common task of video encoding and retrieval And object shape retrieval is in demand in MPEG 7 But current algorithms can not satisfy these requirements, especially on current MPEG 1/2 video data Based on the proposed algorithm WaterShed, a modified method is developed to extract SVO semi automatically, which can get better results when applied to MPEG 1 video stream The major contributions are that the element count is introduced as a classification parameter and that the segmentation is carried out twice on the compressed area and decoded image In experiments, the modified algorithm is more robust and quicker than the proposed one It can extract VO (video object) with velvet contour, which can be used in the shape retrieval and the important object retrieval