Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/99308
標題: Spatiotemporal Coherence-Based Annotation Placement for Surveillance Videos
作者: Wei-Cheng Wang
Chien-Yu Chiou
Chun-Rong Huang
Pau-Choo Chung
Wei-Yun Huang
黃春融
關鍵字: Feature representation;Markov random fields (MRFs);video surveillance
出版社: IEEE Transactions on Circuits and Systems for Video Technology
Project: IEEE Transactions on Circuits and Systems for Video Technology ( Volume: 28 , Issue: 3 , March 2018 )
摘要: 
In this paper, we propose a novel annotation placement approach for revealing information about foreground objects in surveillance videos. To arrange positions of annotations, spatiotemporal coherence between annotations and foreground objects is applied. The annotation placement problem is formulated as an optimization problem with respect to spatiotemporal coherence of annotations and foreground objects. The optimization problem is effectively solved using Markov random fields. To the best of our knowledge, this paper is the first work that discusses and solves the annotation placement problem for surveillance videos by considering the relationships between annotations and foreground objects with trajectories. As shown in the experiments, the proposed approach can arrange annotations based on the moving trajectories of foreground objects and prevent the occlusions between different annotations and foreground objects. It also achieves better quantitative and qualitative results compared with state-of-the-art approaches.
URI: http://hdl.handle.net/11455/99308
DOI: 10.1109/TCSVT.2016.2629340
Appears in Collections:資訊科學與工程學系所

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