Moving Object Segmentation Using Binary Level Set Based on Shape Constraint and Local Evolution
Zheng Jin Xian Shu Li Bo
(Beijing Key Laboratory of Digital Media, Beihang University, Beijing 100191, China)
(The State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China)
Abstract：In order to solve over-segmentation issue and improve computing efficiency, this paper proposes a moving object segmentation model using binary level set based on shape constraint and local curve evolution. Firstly, the model introduces priori shape information in the traditional level set model to constrain segmentation, and the shape is obtained by object detection. Then, to improve efficiency the proposed model uses a binary level set function to replace the traditional level set function. Furthermore, the paper proposes a method of local curve evolution to address the lack of gradual progress in binary level set curve evolution. Finally, the experimental results show that an obvious performance improvement on segmentation could be obtained through the algorithm.
郑锦, 仙树, 李波. 基于形状约束和局部演化的二值水平集运动目标分割[J]. 电子与信息学报, 2013, 35(5): 1037-1043.
Zheng Jin, Xian Shu, Li Bo. Moving Object Segmentation Using Binary Level Set Based on Shape Constraint and Local Evolution. , 2013, 35(5): 1037-1043.
2013, Vol. 35 
