基于边界搜索的运动对象快速凸壳分割算法  

Fast moving objects segmentation algorithm based on boundary searching with convex hull

作　　者：钱增磊[1] 梁久祯[1] 

机构地区：[1]江南大学物联网工程学院,江苏无锡214122

出　　处：《计算机应用》2014年第10期2976-2981,共6页journal of Computer Applications

基　　金：国家自然科学基金资助项目(61170121)

摘　　要：目前在H.264/AVC压缩域分割领域中常用方法造成局部运动矢量(MV)缺失,而通过全局运动补偿来还原运动矢量导致其时间复杂度提高。为解决此问题,提出一种基于边界聚类的快速凸壳分割(BS-CHSTF)算法。该方法主要利用码流中的运动矢量场信息进行分割,首先,对MV利用时空域滤波(STF)对运动矢量进行预处理,采用八方向自适应搜索算法进行边界搜索确定运动连通域;然后根据每个连通域边界求解凸壳并对其进行连通域填充,之后利用运动矢量与距离信息设定聚类规则,对多个连通域进行聚类;最后,对其进行优化掩膜达到分割运动对象的效果。实验结果表明,与混合高斯模型(GMM)分割算法和压缩域蚁群算法(ACA)比较,在分割准确率上平均提高了近3%,甚至在运动矢量场严重缺失的情况下,提高了近20%;而在分割速度上平均提高了近25%。该方法着重于求得运动对象的完整性与快速性,在运动对象不完整的情况下,能够获得较好分割精准度。Most of current segmentation algorithms in H. 264/AVC compressed domain lose the local Motion Vector （MV） field and have high time complexity because of global motion compensation. A new fast segmentation algorithm, called Convex Hull segmentation in Spatial-Temporal Filter （STF） based on Boundary Search on compressed domain （BS-CHSTF） was proposed. Motion vector field in bit stream was mainly used in this algorithm. Firstly, the STF algorithm was used in preprocessing the MV, and then eight-direction adaptive search algorithm was used to get connected region, which is filled by constructing the convex hull using boundary of the connected region. Afterwards, multiple connected regions were clustered by redefining the distance between connected regions distance. Finally, the motion object segmentation was obtained by optimizing the mask. Compared with Gaussian Mixture Model （GMM） segmentation algorithm and Ant Colony Algorithm （ACA）, the experimental results show that the segmentation accuracy is improved about 3% averagely, and even in the case of lack of motion vector field, the segmentation accuracy increased nearly 20%, while the segmentation speed increased an average of nearly 25%. The method focuses on obtaining the moving object quickly with better segmentation accuracy even in the case of Moving Object （MO） uncompleted.

关 键 词：压缩域 快速分割 运动矢量 凸壳 边界搜索 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]