A methodology to evaluate the effect of video compression on the performance of analytics systems

Anastasia Tsifouti; Moustafa M. Nasralla; Manzoor Razaak; James Cope; James M. Orwell; Maria G. Martini; Kingsley Sage

doi:10.1117/12.974618

30 October 2012 A methodology to evaluate the effect of video compression on the performance of analytics systems

Anastasia Tsifouti, Moustafa M. Nasralla, Manzoor Razaak, James Cope, James M. Orwell, Maria G. Martini, Kingsley Sage

Proceedings Volume 8546, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence VIII; 85460S (2012) https://doi.org/10.1117/12.974618
Event: SPIE Security + Defence, 2012, Edinburgh, United Kingdom

Abstract

The Image Library for Intelligent Detection Systems (i-LIDS) provides benchmark surveillance datasets for analytics systems. This paper proposes a methodology to investigate the effect of compression and frame-rate reduction, and to recommend an appropriate suite of degraded datasets for public release. The library consists of six scenarios, including Sterile Zone (SZ) and Parked Vehicle (PV), which are investigated using two different compression algorithms (H.264 and JPEG) and a number of detection systems. PV has higher spatio-temporal complexity than the SZ. Compression performance is dependent on scene content hence PV will require larger bit-streams in comparison with SZ, for any given distortion rate. The study includes both industry standard algorithms (for transmission) and CCTV recorders (for storage). CCTV recorders generally use proprietary formats, which may significantly affect the visual information. Encoding standards such as H.264 and JPEG use the Discrete Cosine Transform (DCT) technique, which introduces blocking artefacts. The H.264 compression algorithm follows a hybrid predictive coding approach to achieve high compression gains, exploiting both spatial and temporal redundancy. The highly predictive approach of H.264 may introduce more artefacts resulting in a greater effect on the performance of analytics systems than JPEG. The paper describes the two main components of the proposed methodology to measure the effect of degradation on analytics performance. Firstly, the standard tests, using the ‘f-measure’ to evaluate the performance on a range of degraded video sets. Secondly, the characterisation of the datasets, using quantification of scene features, defined using image processing techniques. This characterization permits an analysis of the points of failure introduced by the video degradation.

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Anastasia Tsifouti, Moustafa M. Nasralla, Manzoor Razaak, James Cope, James M. Orwell, Maria G. Martini, and Kingsley Sage "A methodology to evaluate the effect of video compression on the performance of analytics systems", Proc. SPIE 8546, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence VIII, 85460S (30 October 2012); https://doi.org/10.1117/12.974618

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