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Video compression technique impact on efficiency of person identification in CCTV systems

Vitek, Stanislav, Klima, Milos, Krasula, Lukas·2014·2014 International Carnahan Conference on Security Technology (ICCST)
DOI 10.1109/ccst.2014.6987027
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Abstract

Recently, High Efficiency Video Coding (HEVC or H.265) standard becomes to be widely applied and exploited. This compression standard can achieve very low video bitrates and allow deployment of mobile security cameras with wireless data transmission. The paper deals with subjective evaluation and assessment of the above mentioned standard and its impact on reliability and efficiency of person identification under very low video bitrate condition. The evaluation procedure is based upon modified test with reference when the separate reference database of persons appearing the testing video sequences is available. The reference database is a set of standard portrait photos. Results of the paper show applicability of HEVC compression standard in the security CCTV camera systems especially in comparison with earlier widely used standards as H.264.

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Crossref · 10.1109/ccst.2014.6987027

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  • Vitek et al. found correct identifications decreased from 88 to 48% as HEVC encoding quality decreased (30 kbps-15 kpbs) and recommend 20 Kbps as a minimum threshold value.

    “Vitek et al. [125] found correct identifications decreased from 88 to 48% as HEVC encoding quality decreased (30 kbps–15 kpbs) and they recommend 20 Kbps as a minimum threshold value.”

    From Forensic Facial Comparison: Current Status, Limitations, and Future Directions (2021) · cites this paper as [125]

  • Vitek et al. recalculate Utochkin's recommendations to 35 pixels for a known individual and 83 pixels for an unknown individual.

    “Based on relative subject size on screen, Vitek et al. [125] recalculate Utochkin’s [126] recommendations to 35 pixels for a known individual and 83 pixels for an unknown individual.”

    From Forensic Facial Comparison: Current Status, Limitations, and Future Directions (2021) · cites this paper as [125]

  • Both the FISWG and the ENFSI recommend MA as the best practice for forensic facial identification.

    “Both the FISWG and the ENFSI recommend MA as the best practice for forensic facial identification [27,125].”

    From Forensic Facial Comparison: Current Status, Limitations, and Future Directions (2021) · cites this paper as [125]

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Research works printed but not linked: 27

  1. 10.1111/1467-9280.00144 · DOI · Paper page
  2. 10.1111/j.2044-8295.1986.tb02199.x · DOI
  3. 10.3758/BF03213093 · DOI · Paper page
  4. 10.1371/journal.pone.0002590 · DOI
  5. 10.1117/12.766343 · DOI · Paper page
  6. 10.1109/CCST.2004.1405405 · DOI
  7. 10.1109/DICTA.2009.41 · DOI
  8. 10.1117/12.774212 · DOI · Paper page
  9. 10.1117/12.2004140 · DOI
  10. 10.1109/CCST.2013.6922066 · DOI
  11. ribeiro, 2005, Human activity recognition from video: modeling, feature selection and classification architecture, Proc Int Workshop Human Activity Recognition and Modeling, 61
  12. 0, Guidelines for identification, CCTV Advisory Service
  13. lv, 2004, Automatic tracking and labeling of human activities in a video sequence, Proc Int Workshop Performance Evaluation of Tracking and Surveillance
  14. 10.1109/TSMCB.2007.907036 · DOI
  15. 10.1109/MMCS.1999.778358 · DOI
  16. 10.1109/TPAMI.2009.59 · DOI
  17. 10.1109/MC.2010.37 · DOI
  18. 10.1109/MC.2012.97 · DOI
  19. 10.1109/JPROC.2006.884093 · DOI · Paper page
  20. 10.5772/31519 · DOI
  21. 10.1109/TCE.2014.6780933 · DOI
  22. hanhart, 2012, Subjective quality evaluation of the upcoming HEVC video compression standard, Applications of Digital Image Processing XXXV Proc SPIE, 8499, 10.1117/12.946036 · DOI
  23. 10.1109/TCSVT.2012.2221191 · DOI
  24. 10.1117/12.774212 · DOI · Paper page
  25. 10.1109/TCSVT.2012.2221255 · DOI
  26. utochkin, 0, The principles of CCTV design in VideoCAD, Part II Person detection area person identification area license plate reading area Spatial resolution Edition for VideoCAD 7
  27. utochkin, 0, The principles of CCTV design in VideoCAD, Part I Camera view area Edition for VideoCAD 7

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Metadata

Authors
Vitek, S., Klima, M., & Krasula, L.
Venue
2014 International Carnahan Conference on Security Technology (ICCST)
Publisher
IEEE
Published
2014-10
Pages
1-5
DOI
10.1109/ccst.2014.6987027
Cited by
4
References
0

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