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Customizing Multiprocessor Implementation of an Automated Video Surveillance System

EURASIP Journal on Embedded Systems volume 2006, Article number: 045758 (2006) Cite this article

Abstract

This paper reports on the development of an automated embedded video surveillance system using two customized embedded RISC processors. The application is partitioned into object tracking and video stream encoding subsystems. The real-time object tracker is able to detect and track moving objects by video images of scenes taken by stationary cameras. It is based on the block-matching algorithm. The video stream encoding involves the optimization of an international telecommunications union (ITU)-T H.263 baseline video encoder for quarter common intermediate format (QCIF) and common intermediate format (CIF) resolution images. The two subsystems running on two processor cores were integrated and a simple protocol was added to realize the automated video surveillance system. The experimental results show that the system is capable of detecting, tracking, and encoding QCIF and CIF resolution images with object movements in them in real-time. With low cycle-count, low-transistor count, and low-power consumption requirements, the system is ideal for deployment in remote locations.

[1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33]

References

  1. El-Azim SA, Ismail I, El-Latiff HA: An efficient object tracking technique using block-matching algorithm. Proceedings of the 9th National Radio Science Conference (NRSC '02), March 2002, Alexandria, Egypt 427-433.

    Chapter  Google Scholar 

  2. Mahmoud II, Abd El-Halym HA, Habib SE-D: Hardware development and implementation of an object tracking algorithm. Proceedings of the 15th International Conference on Microelectronics (ICM '03), December 2003, Cairo, Egypt 330-334.

    Google Scholar 

  3. Lehtoranta O, Hämäläinen T, Saarinen J: Parallel implementation of H.263 encoder for CIF-sized images on quad DSP system. Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS '01), May 2001, Sydney, Australia 2: 209-212.

    Google Scholar 

  4. Chang Y-C, Chao W-M, Chen L-G: LSI design for MPEG-4 coding system. Proceedings of 47th Midwest Symposium on Circuits and Systems (MWSCAS '04), July 2004, Hiroshima, Japan 2: 453-456.

    Google Scholar 

  5. Garrido MJ, Sanz C, Jiménez M, Meneses JM: A flexible architecture for H.263 video coding. Journal of Systems Architecture 2003,49(12–15):641-661. 10.1016/S1383-7621(03)00094-8

    Article  Google Scholar 

  6. Kim J-G, Jay Kuo C-C: MPEG-4 video codec IP design with a configurable embedded processor. Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS '03), May 2003, Bangkok, Thailand 2: 776-779.

    Google Scholar 

  7. Cheung S-CS, Kamath C: Robust techniques for background subtraction in urban traffic video. Visual Communications and Image Processing, January 2004, San Jose, Calif, USA, Proceedings of SPIE 5308: 881-892.

    Google Scholar 

  8. Cucchiara R, Grana C, Piccardi M, Prati A: Detecting moving objects, ghosts, and shadows in video streams. IEEE Transactions on Pattern Analysis and Machine Intelligence 2003,25(10):1337-1342. 10.1109/TPAMI.2003.1233909

    Article  Google Scholar 

  9. Cutler R, Davis LS: View-based detection and analysis of periodic motion. In Proceedings of the 14th International Conference on Pattern Recognition (ICPR '98) , August 1998, Brisbane, Queensland, Australia. Volume 1. IEEE Computer Society Press; 495-500.

    Google Scholar 

  10. Elgammal A, Duraiswami R, Harwood D, Davis LS: Background and foreground modeling using nonparametric kernel density estimation for visual surveillance. Proceedings of the IEEE 2002,90(7):1151-1163. 10.1109/JPROC.2002.801448

    Article  Google Scholar 

  11. McFarlane NJB, Schofield CP: Segmentation and tracking of piglets in images. Machine Vision and Applications 1995,8(3):187-193. 10.1007/BF01215814

    Article  Google Scholar 

  12. Wren CR, Azarbayejani A, Darrell T, Pentland AP: Pfinder: real-time tracking of the human body. IEEE Transactions on Pattern Analysis and Machine Intelligence 1997,19(7):780-785. 10.1109/34.598236

    Article  Google Scholar 

  13. Heikkila J, Silven O: A real-time system for monitoring of cyclists and pedestrians. Proceedings of the 2nd IEEE Workshop on Visual Surveillance (VS '99), July 1999, Collins, Colo, USA 74-81.

    Chapter  Google Scholar 

  14. Stauffer C, Grimson WEL: Learning patterns of activity using real-time tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence 2000,22(8):747-757. 10.1109/34.868677

    Article  Google Scholar 

  15. Stauffer C, Grimson WEL: Adaptive background mixture models for real-time tracking. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '99), June 1999, Fort Collins, Colo, USA 2: 246-252.

    Article  Google Scholar 

  16. Hariharakrishnan K, Schonfeld D, Raffy P, Yassa F: Video tracking using block matching. Proceedings of IEEE International Conference on Image Processing (ICIP '03), September 2003, Barcelona, Spain 3: 945-948.

    Google Scholar 

  17. Hariharakrishnan K, Schonfeld D, Raffy P, Yassa F: Object tracking using adaptive block matching. Proceedings of the International Conference on Multimedia and Expo (ICME '03), July 2003, Baltimore, Md, USA 3: 65-68.

    Google Scholar 

  18. ITU-T experts group on very bitrate visual telephony, ITU-T Recommendation H.263 version 2: video coding for low bitrate communication, January 1998

  19. Yu N, Kim K, Salcic Z: A new motion estimation algorithm for mobile real-time video and its FPGA implementation. Proceedings of IEEE Region 10 International Conference on Electrical and Electronic Technology (TENCON '04), November 2004, Chiang Mai, Thailand A: 383-386.

    Google Scholar 

  20. Gonzalez RE: Xtensa: a configurable and extensible processor. IEEE Micro 2000,20(2):60-70. 10.1109/40.848473

    Article  Google Scholar 

  21. Aalmoes R: Roalt's H.263 Page. October 2003, http://www.xs4all.nl/~roalt/h263.html

  22. Arizona State University : YUV 4:2:0 video sequences. nd; http://trace.eas.asu.edu/yuv/index.html

  23. Massimino P: Implementing a Fast DCT/IDCT with SIMD Instructions. July 2002

  24. Loeffer C, Ligtenberg A, Moschytz GS: Practical fast 1-D DCT algorithms with 11 multiplications. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '89), May 1989, Glasgow, Scotland 2: 988-991.

    Google Scholar 

  25. Arai Y, Agui T, Nakajima M: A fast DCT-SQ scheme for images. Transactions of the Institute of Electronics, Information and Communication Engineers E 1988,E71(11):1095-1097.

    Google Scholar 

  26. Wang G: Real-time multiprocessor implementation of an automated video surveillance application, ME thesis. The University of Auckland, Auckland, New Zealand; 2005.

    Google Scholar 

  27. Wren CR, Azarbayejani A, Darrell T, Pentland AP: Pfinder: real-time tracking of the human body. IEEE Transactions on Pattern Analysis and Machine Intelligence 1997,19(7):780-785. 10.1109/34.598236

    Article  Google Scholar 

  28. Fisher B, Perkins S, Walker A, Wolfart E: Adaptive Thresholding. 1994, http://www.cee.hw.ac.uk/hipr/html/adpthrsh.html

  29. Rosenfeld A, Pfaltz JL: Sequential operations in digital picture processing. Journal of the ACM 1966,13(4):471-494. 10.1145/321356.321357

    Article  MATH  Google Scholar 

  30. Bramberger M, Brunner J, Rinner B, Schwabach H: Real-time video analysis on an embedded smart camera for traffic surveillance. Proceedings of 10th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS '04), May 2004, Toronto, Canada 10: 174-181.

    Google Scholar 

  31. Tensilica Inc Xtensa Instruction Set Simulator (ISS) User's Guide (For Xtensa T1050.2 Processor Cores), 2003

  32. Nagel HH: Institut für Algorithmen und Kognitive Systeme. nd; http://i21www.ira.uka.de/image_sequences/

  33. Lee A: virtualdub.org. nd; http://www.virtualdub.org

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand

    Gary Wang, Zoran Salcic & Morteza Biglari-Abhari

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  1. Gary Wang
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  2. Zoran Salcic
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  3. Morteza Biglari-Abhari
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Correspondence to Gary Wang.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Wang, G., Salcic, Z. & Biglari-Abhari, M. Customizing Multiprocessor Implementation of an Automated Video Surveillance System. J Embedded Systems 2006, 045758 (2006). https://doi.org/10.1155/ES/2006/45758

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