This paper examines a new problem in large scale stream data: abnormality detection which is localized to a data segmentation process. Unlike traditional abnormality detection methods which typically build one unified...
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ISBN:
(纸本)9781467322164
This paper examines a new problem in large scale stream data: abnormality detection which is localized to a data segmentation process. Unlike traditional abnormality detection methods which typically build one unified model across data stream, we propose that building multiple detection models focused on different coherent sections of the video stream would result in better detection performance. One key challenge is to segment the data into coherent sections as the number of segments is not known in advance and can vary greatly across cameras; and a principled way approach is required. To this end, we first employ the recently proposed infinite HMM and collapsed Gibbs inference to automatically infer data segmentation followed by constructing abnormality detection models which are localized to each segmentation. We demonstrate the superior performance of the proposed framework in a real-world surveillance camera data over 14 days.
Almost every aspect of how we create, transmit, and consume video has changed, but video interfaces still mimic those from video's inception. We extend Temporal Semantic Compression for interactive video browsing,...
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Almost every aspect of how we create, transmit, and consume video has changed, but video interfaces still mimic those from video's inception. We extend Temporal Semantic Compression for interactive video browsing, which uses an arbitrary frame-by-frame interest measure to sub-sample video in real time, with user interface elements that visualize these measures and the effect of compressing on them. We experiment with a novel interest measure for popularity, and design novel visualizations for expressing interest measures and the compression interaction. We conduct the first formative evaluation of the TSC paradigm, with 8 subjects, and report design implications arising from it.
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