Motion connectivity-based initial video object extraction

摘要

为了从视频序列中获取初始视频对象,提出了一种改进的基于运动连通性的初始视频对象提取算法．视频中的运动对象高度连通结构化,这就使得运动连通性是适用于视频对象分割的高级特征．据此首先对反映对象的一致性运动的累计帧差图进行尖锐噪声滤除,然后应用自适应阈值算法提取对象运动区域,接着根据运动连通性标记出最大连通区域,通过后处理得到视频对象的分割模版从而有效提取出初始视频对象．对比实验结果表明,该算法能自动、快速、准确地提取出初始视频对象,获得了理想的主客观分割效果．%In order to obtain the initial video objects from the video sequences, an improved initial video object extraction algorithm based on motion connectivity is proposed. Moving objects in video sequences are highly connected and structured, which makes motion connectivity an advanced feature for segmentation. Accordingly, after sharp noise elimination, the cumulated difference image, which exhibits the coherent motion of the moving object, is adaptively thresholded. Then the maximal connected region is labeled, post-processed and output as the final segmenting mask. Hence the initial video object is effectively extracted. Comparative experimental results show that the proposed algorithm extracts the initial video object automatically, promptly and properly, thereby achieving satisfactory subjective and objective performance.