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ANOMALY DETECTION USING A KERNEL-BASED SPARSE RECONSTRUCTION MODEL
ANOMALY DETECTION USING A KERNEL-BASED SPARSE RECONSTRUCTION MODEL
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机译：基于核的稀疏重建模型的异常检测
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摘要
A method and system for detecting anomalies in video footage. A training dictionary can be configured to include a number of event classes, wherein events among the event classes can be defined with respect to n-diminensional feature vectors. One or more nonlinear kernel function can be defined, which transform the n-dimensional feature vectors into a higher dimensional feature space. One or more test events can then be received within an input video sequence of the video footage. Thereafter, a determination can be made if the test event(s) is anomalous by applying a sparse reconstruction with respect to the training dictionary in the higher dimensional feature space induced by the nonlinear kernel function.
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