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Detection of Abnormal Event in Complex Situations Using Strong Classifier Based on BP Adaboost

机译:基于BP Adaboost的强分类器在复杂情况下的异常事件检测

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摘要

In order to recognize the abnormal event, such as emergency or panic, happened in public scenes timely, an algorithm based on features extraction and BP Adaboost to detect abnormal frame event from surveillance video of complex situation is proposed. The proposed method detects an abnormal event where people are running, and this panic situation is simulated by the frame in a video. Experiments show that the method can distinguish and detect the abnormal event effectively and efficiently, which has potentiality to be used in the real public monitoring.
机译:为了及时识别在公共场所发生的紧急事件或紧急事件等异常事件,提出了一种基于特征提取和BP Adaboost的复杂场景监控视频异常帧事件检测算法。所提出的方法检测到有人在奔跑的异常事件,并且通过视频中的帧来模拟这种恐慌情况。实验表明,该方法能够有效,高效地识别和检测异常事件,具有在实际的公共监控中使用的潜力。

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