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Anomaly detection in compressed H.264/AVC video

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Abstract

Real time anomaly detection is the need of the hour for any security applications. In this article, we have proposed a real time anomaly detection for H.264 compressed video streams utilizing pre-encoded motion vectors (MVs). The proposed work is principally motivated by the observation that MVs have distinct characteristics during anomaly than usual. Our observation shows that H.264 MV magnitude and orientation contain relevant information which can be used to model the usual behavior (UB) effectively. This is subsequently extended to detect abnormality/anomaly based on the probability of occurrence of a behavior. The performance of the proposed algorithm was evaluated and bench-marked on UMN and Ped anomaly detection video datasets, with a detection rate of 70 frames per sec resulting in 90× and 250× speedup, along with on-par detection accuracy compared to the state-of-the-art algorithms.

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Authors and Affiliations

  1. Video Analytics Lab, Supercomputer Education and Research Center, Indian Institute of Science, Bangalore, 560012, India

    Sovan Biswas & R. Venkatesh Babu

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  1. Sovan Biswas
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  2. R. Venkatesh Babu
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Correspondence to R. Venkatesh Babu.

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Biswas, S., Babu, R.V. Anomaly detection in compressed H.264/AVC video. Multimed Tools Appl 74, 11099–11115 (2015). https://doi.org/10.1007/s11042-014-2219-4

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  • DOI: https://doi.org/10.1007/s11042-014-2219-4

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