Importance

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Abstract

Methods and apparatus to detect anomalies in video data are disclosed. An example apparatus disclosed herein generates a reconstructed feature vector corresponding to an input feature vector representative of a video segment, the reconstructed feature vector based on a transformation applied to the input feature vector and an inverse of the transformation applied to an output of the transformation, the input feature vector and the reconstructed feature vector including features associated with a plurality of dimensions including a time dimension. The disclosed example apparatus also generates an error vector based on a difference between the input feature vector and the reconstructed feature vector. The disclosed example apparatus further generates an anomaly map based on sums of elements of the error vector across at least the time dimension, the anomaly map corresponding to the video segment.

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First Claim