Compressed Domain Moving Object Detection based on H.264/AVC Macroblock Types

Marcus Laumer, Peter Amon, Andreas Hutter, André Kaup

2013

Abstract

This paper introduces a low complexity frame-based object detection algorithm for H.264/AVC video streams. The method solely parses and evaluates H.264/AVC macroblock types extracted from the video stream, which requires only partial decoding. Different macroblock types indicate different properties of the video content. This fact is used to segment a scene in fore- and background or, more precisely, to detect moving objects within the scene. The main advantage of this algorithm is that it is most suitable for massively parallel processing, because it is very fast and combinable with several other pre- and post-processing algorithms, without decreasing their performance. The actual algorithm is able to process about 3600 frames per second of video streams in CIF resolution, measured on an Intel R CoreTM i5-2520M CPU @ 2.5 GHz with 4 GB RAM.

References

  1. Berclaz, J., Fleuret, F., Turetken, E., and Fua, P. (2011). Multiple Object Tracking Using K-Shortest Paths Optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(9):1806-1819.
  2. Comaniciu, D. and Meer, P. (2002). Mean Shift: A Robust Approach Toward Feature Space Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(5):603-619.
  3. Fei, W. and Zhu, S. (2010). Mean Shift Clustering-based Moving Object Segmentation in the H.264 Compressed Domain. IET Image Processing, 4(1):11-18.
  4. Laumer, M., Amon, P., Hutter, A., and Kaup, A. (2011). A Compressed Domain Change Detection Algorithm for RTP Streams in Video Surveillance Applications. In Proc. IEEE 13th Int. Workshop on Multimedia Signal Processing (MMSP), pages 1-6.
  5. Mak, C.-M. and Cham, W.-K. (2009). Real-time Video Object Segmentation in H.264 Compressed Domain. IET Image Processing, 3(5):272-285.
  6. MPEG (2010). ISO/IEC 14496-10:2010 - Coding of AudioVisual Objects - Part 10: Advanced Video Coding.
  7. Poppe, C., De Bruyne, S., Paridaens, T., Lambert, P., and Van de Walle, R. (2009). Moving object detection in the H.264/AVC compressed domain for video surveillance applications. Journal of Visual Communication and Image Representation, 20(6):428-437.
  8. Porikli, F., Bashir, F., and Sun, H. (2010). Compressed Domain Video Object Segmentation. IEEE Transactions on Circuits and Systems for Video Technology, 20(1):2-14.
  9. Qiya, Z. and Zhicheng, L. (2009). Moving Object Detection Algorithm for H.264/AVC Compressed Video Stream. In Proc. Int. Colloquium on Computing, Communication, Control, and Management (CCCM), volume 1, pages 186-189.
  10. Szczerba, K., Forchhammer, S., Stottrup-Andersen, J., and Eybye, P. T. (2009). Fast Compressed Domain Motion Detection in H.264 Video Streams for Video Surveillance Applications. In Proc. Sixth IEEE Int. Conf. on Advanced Video and Signal Based Surveillance (AVSS), pages 478-483.
  11. VCEG (2011). H.264: Advanced Video Coding for Generic Audiovisual Services.
  12. Verstockt, S., De Bruyne, S., Poppe, C., Lambert, P., and Van de Walle, R. (2009). Multi-view Object Localization in H.264/AVC Compressed Domain. In Proc. Sixth IEEE Int. Conf. on Advanced Video and Signal Based Surveillance (AVSS), pages 370-374.
  13. Wang, R., Zhang, H.-J., and Zhang, Y.-Q. (2000). A Confidence Measure Based Moving Object Extraction System Built for Compressed Domain. In Proc. IEEE Int. Symp. on Circuits and Systems (ISCAS), volume 5, pages 21-24.
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Paper Citation


in Harvard Style

Laumer M., Amon P., Hutter A. and Kaup A. (2013). Compressed Domain Moving Object Detection based on H.264/AVC Macroblock Types . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 219-228. DOI: 10.5220/0004296602190228


in Bibtex Style

@conference{visapp13,
author={Marcus Laumer and Peter Amon and Andreas Hutter and André Kaup},
title={Compressed Domain Moving Object Detection based on H.264/AVC Macroblock Types},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={219-228},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004296602190228},
isbn={978-989-8565-47-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - Compressed Domain Moving Object Detection based on H.264/AVC Macroblock Types
SN - 978-989-8565-47-1
AU - Laumer M.
AU - Amon P.
AU - Hutter A.
AU - Kaup A.
PY - 2013
SP - 219
EP - 228
DO - 10.5220/0004296602190228