Segmentation of multiple moving object in an image sequence is one of the most challenging problems in image processing due to the complexity of its motion.This paper presents a novel multiple object segmentation algorithm based on spatial-temporal curve evolution.First

According to the dissimilar characteristic of the intra-frame and inter-frame (Spatial and Temporal) information

a joint energy model is proposed with global and local features

thus

a curve evolution equation could be achieved based on the method of level sets.Then

an initial object model is achieved with the difference between two successive frames

multiple objects are tracked and extracted with spatio-temporal curve evolution.Finally

while the occlusion is emerged due to multiple object overlapping motion

the objects could be segmented using Bayes classification for minimum error.The experiment results show that the algorithm is effective.