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• W4323020851 abstract "Recently, many video monitoring systems utilize deep learning technologies to recognize locations and trajectories of people in video data. In video monitoring systems, a fast discovery of human groups is an important task for several applications, for example, crime surveillance, contact tracing, and customer behavior analysis. To tackle the demand, we propose a group tracking method. First, we propose a spatial proximity definition and define a novel query type, a group tracking query that considers characteristics of video data. A group tracking query retrieves the groups that travel for more than a certain amount of video frame within a certain distance. We propose an efficient query processing method that exploits the spatio-temporal characteristics of groups. Through extensive experiments using real-world datasets, we verify the efficiency and effectiveness of our query definition and query processing method." @default.
• W4323020851 created "2023-03-04" @default.
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• W4323020851 date "2023-01-01" @default.
• W4323020851 modified "2023-09-29" @default.
• W4323020851 title "Group Tracking for Video Monitoring Systems: A Spatio-Temporal Query Processing Approach" @default.
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• W4323020851 doi "https://doi.org/10.1109/access.2023.3249190" @default.
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