Multiple Video Object Segmentation Based on Maximization of the A Posteriori Probability of Spatio-Temporal Label Field
基于时空标记场最大后验概率的多视频对象分割算法

This paper presents a novel multiple object segmentation algorithm based on a Bayesian framework. According to the characteristic of the intra-frame and inter-frame (spatial and temporal) information, a representation of Maximization of the A posteriori Probability(MAP) of spatio-temporal label field is proposed. So a minimization of energy function is obtained. The optimization of solution is carried out by Iterated Conditional Mode(ICM) method. The initial segmentation label fields is gotten using vector histogram. The experimental results show that the algorithm is effective to multiple object segmentation with partial occlusion.