基于运动连通性二维网格运动分析的视频对象分割算法

提出了一种基于运动连通性二维网格运动分析的视频对象时空分割算法。该算法首先利用特征检测算法获得视频帧图像的自适应二维网格表示，然后利用基于运动连通性的高阶统计方法对二维网格表示进行运动分析快速获得粗糙的运动轮廓区域并进行边缘精细化，接着对根据连通性标注出的最大连通区域进行后处理就能获得最终的分割模板从而有效提取出视频对象。实验结果表明，该算法综合了网格基分割算法和像素基分割算法的优点，具有理想的主客观性能，提高了分割速度。

Video object segmentation by 2-D mesh-based motion analysis according to motion connectivity

Video object extraction is a key technology in the content-based video coding. A new temporal-spatial video object segmentation algorithm is proposed. This algorithm is based on 2-D mesh-based motion analysis according to motion connectivity. Firstly, a 2-D adaptive mesh fitting the original frame image is obtained via the feature detection algorithm. Then, a higher order statistics motion analysis according to motion connectivity is made of the 2-D mesh representation to get a coarse motion boundary layer. After refining the coarse boundary layer and post-processing the labeled maximal connected region, the final segmenting mask is quickly obtained. Hence the video object is effectively extracted. Experimental results show that the proposed algorithm combines the merits of the mesh-based segmentation algorithms and the pixel-based segmentation algorithms, and therefore achieves satisfactory subjective and objective performance as well as increasing the speed of segmentation.