Automatic spatio-temporal video sequence segmentation
作者： J. Vass , K. Palaniappan , Xinhua Zhuang
关键词: Computer vision 、 Motion estimation 、 Mathematical morphology 、 Segmentation 、 Scale-space segmentation 、 Iterative refinement 、 Computer science 、 Segmentation-based object categorization 、 Dilation (morphology) 、 Minimum spanning tree-based segmentation 、 Artificial intelligence 、 Pattern recognition 、 Image segmentation
摘要: An automatic spatio-temporal video sequence segmentation algorithm is proposed. To address this very difficult computer vision problem, several novel algorithms have been developed which use both spatial and temporal information. First, a based on our previous work in motion estimation. Second, an iterative split-and-merge scheme proposed with initial being provided by recursive conditioned dilation operation merging pixels into homogeneous regions, followed refinement to obtain the final segmentation. Third, are linked form shape of each object simplified morphological close-opening Performance evaluation shows that can successfully segment moving objects without any human intervention.
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