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This paper presents a framework for anomaly detection in videos which considers both motion and appearance features. For motion cues, we propose a new feature called 3D-HOF, which effectively extracts both velocity and orientation from the optical flow map. At the same time, we introduce the concept of “depth of field” problem to make the detection more accurate when the velocity of an object may...
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