首页|Proposals from binary tree and spatio-temporal tunnel for temporal segmentation of rough videos
Proposals from binary tree and spatio-temporal tunnel for temporal segmentation of rough videos
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NETL
NSTL
万方数据
维普
Existing temporal segmentation methods suffer from the problems of high computational complexity and complicated steps.To address this issue,we present a method that combines the binary tree and spatio-temporal tunnel(STT)for temporal segmentation of rough videos.First,we compute initial cumulative spatio-temporal flow to determine flow overflow of sub-video which is divided from a rough video.Second,the decision tree is generated by combining bi-nary tree and balance factor to dynamically adjust the sampling line of the STT.Finally,pixels on the sampling line are extracted to generate an adaptive STT for temporal proposals.Experimental results show that the computational complexity of the proposed method is significantly better than that of the comparison methods while ensuring accu-racy.
ZHANG Yunzuo、GUO Kaina
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School of Information Science and Technology,Shijiazhuang Tiedao University,Shijiazhuang 050043,China
国家自然科学基金国家自然科学基金河北省自然科学基金河北省自然科学基金湖北省教育厅科技项目湖北省教育厅科技项目Central Guidance on Local Science and Technology Development Fund
NETL
NSTL
万方数据
维普
