中文摘要：

与视觉暗示能作为一种刺激被拿的看法，在由最后在他们的概率的表示使用视觉暗示的视觉感觉进程的机制的学习导致多重视觉暗示( IMVC )的统计集成的一个类在感性的组织广泛地被使用了的方法，录像分析，和在计算机视觉的另外的基本问题。在这篇论文，基本想法和 IMVC 方法的最近的进展上的调查被介绍，并且许多焦点在为在贝叶斯的评价的框架以内的录像分析的 IMVC 的模型和算法上。而且，在录像分析，在追踪的多目标(MTT ) 的柔韧的视觉追踪和“切换的问题”的二个典型问题作为测试床被拿验证方法由作者建议了的一系列贝叶斯底的 IMVC。而且，在统计 IMVC 之间的关系和视觉感觉过程，以及潜在的未来研究为 IMVC 工作，被讨论。

英文摘要：

With the view that visual cue could be taken as a kind of stimulus, the study of the mechanism in the visual perception process by using visual cues in their probabilistic representation eventually leads to a class of statistical Integration of multiple visual cues （IMVC） methods which have been applied widely in perceptual grouping, video analysis, and other basic problems in computer vision. In this paper, a survey on the basic ideas and recent advances of IMVC methods is presented, and much focus is on the models and algorithms of IMVC for video analysis within the framework of Bayesian estimation. Furthermore, two typical problems in video analysis, robust visual tracking and “switching problem” in muIti-targèt tracking （MTT） are taken as test beds to verify a series of Bayesian-based IMVC methods proposed by the authors. Furthermore, the relations between the statistical IMVC and the visual perception process, as well as potential future research work for IMVC, are discussed.