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Anomaly Detection In Compressed Video | IEEE Conference Publication | IEEE Xplore

Anomaly Detection In Compressed Video


Abstract:

In this paper, an anomaly detection approach has been developed on video compressed in H.265 format. In order to detect anomalies, the motion vectors in the compressed vi...Show More

Abstract:

In this paper, an anomaly detection approach has been developed on video compressed in H.265 format. In order to detect anomalies, the motion vectors in the compressed video and the region information of the motion vectors were used. This information was provided as input to the autoencoder model, which is an unsupervised artificial neural network method, and thus the model was trained. The trained model was tested on video data containing anomalies. As output, during the streaming of any video, it is provided to draw a regularity score graph and display the anomaly regions by color. In this paper, we propose an autoencoder based method for anomaly detection in compressed video instead of the original uncompressed video.
Date of Conference: 09-11 June 2021
Date Added to IEEE Xplore: 19 July 2021
ISBN Information:
Print on Demand(PoD) ISSN: 2165-0608
Conference Location: Istanbul, Turkey