Designing a Posture Analysis System with Hardware Implementation
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Posture analysis is an active research area in computer vision for applications such as home care and security monitoring. This paper describes the design of a system for posture analysis with hardware acceleration, addressing the following four aspects: (a) a design workflow for posture analysis based on radial shape and projection histogram representations; (b) the implementation of different architectures based on a high-level hardware design approach with support for automating transformations to improve parallelism and resource optimisation; (c) accuracy evaluation of the proposed posture analysis system, and (d) performance evaluation for the derived designs. One of the designs, which targets a Xilinx XC2V6000 FPGA at 90.2 MHz, is able to perform posture analysis at a rate of 1,164 frames per second with a frame size of 320 by 240 pixels. It represents 3.5 times speedup over optimised software running on a 2.4 GHz AMD Athlon 64 3700+ computer. The frame rate is well above that of real-time video, which enables the sharing of the FPGA among multiple video sources.
Keywordsposture analysis gait analysis hardware compilation FPGA ubiquitous sensor networks
The support of DTI Next Wave Programme, Fundação para a Ciência e Tecnologia (Grant number SFRH/BD/3354/2000), UK Engineering and Physical Sciences Research Council (Grant number EP/C 509625/1 and EP/C 549481/1), Celoxica Limited and Xilinx, Inc. is gratefully acknowledged. Furthermore, we thank the reviewers for their useful suggestions.
- 1.Advanced Micro Devices (AMD) Inc., http://www.amd.com.
- 2.A. Azarbayejani, C. Wren, and A. Pentland, “Real-time 3D Tracking of the Human Body,” in Proc. of IMAGE’COM 96, 1996.Google Scholar
- 3.T. Boult, “Frame-rate Multibody Tracking for Surveillance,” in Proc. of DARPA Image Understanding Workshop, 1998.Google Scholar
- 4.Celoxica Ltd, http://www.celoxica.com/.
- 5.C. C. Cheung, W. Luk, and P. Y. K. Cheung, “Reconfigurable Elliptic Curve Cryptosystem on a Chip,” in Proc. Int. Conf. on Design Automation and Test in Europe (DATE), vol. 1, 2005, pp. 24–29.Google Scholar
- 6.J. G. F. Coutinho, J. Jiang, and W. Luk, “Interleaving Behavioural and Cycle-accurate Descriptions for Reconfigurable Hardware Compilation,” in IEEE Symposium on Field-Programmable Custom Computing Machines, 2005.Google Scholar
- 9.E. Grimson and C. Stauffer, “Adaptive Background Mixture Models for Real Time Tracking,” in Proc. of the Computer Vision and Pattern Recognition Conference, 1999.Google Scholar
- 11.Intel Corporation, http://www.intel.com.
- 12.M. P. T. Juvonen, J. G. F. Coutinho, J. L. Wang, B. L. Lo, W. Luk, O. Mencer, and G. Z. Yang, “Custom Hardware Architectures for Posture Analysis,” in IEEE International Conference on Field Prog. Tech., 2005.Google Scholar
- 13.A. Lipton, H. Fujiyoshi, and H. Patil, “Moving Target Detection and Classification from Real-time Video,” in Proc. of the IEEE Workshop Application of Computer Vision, 1998.Google Scholar
- 14.B. Lo, J. L. Wang, and G. Z. Yang, “From Imaging Networks to Behavior Profiling: Ubiquitous Sensing for Managed Homecare of the Elderly,” in Adjunct Proc. of the 3rd International Conference on Pervasive Computing, May 2005.Google Scholar
- 15.W. Luk, T. K. Lee, J. R. Rice, P. Y. K. Cheung, and N. Shirazi, “Reconfigurable Computing for Augmented Reality,” in Proc. of the IEEE Symposium on Field-Programmable Custom Computing Machines, 1999, pp. 136–145.Google Scholar
- 17.T. Olson and F. Brill, “Moving Object Detection and Event Recognition Algorithms for Smart Cameras,” in Proc. of DARPA Image Understanding Workshop, 1997, pp. 159–175.Google Scholar
- 18.J. M. Rehg, M. Loughlin, and K. Waters, “Vision for a Smart Kiosk,” in IEEE Conference Computer Vision and Pattern Recognition, 1997.Google Scholar
- 20.TriMedia TM1300, http://www.tm1300.com/.
- 22.J. Villasenor, B. Schoner, K. Chia, and C. Zapata, “Configurable Computing Solutions for Automatic Target Recognition,” in Proc. IEEE Symposium on FPGAs for Custom Computing Machines, 1996, pp. 70–79.Google Scholar
- 24.C. Wren, A. Azarbayejani, T. Darrell, and A. Pentland, “Pfinder: Real-time Tracking of the Human Body,” in Pfinder: Real-time Tracking of the Human Body, vol. 19, no. 7, 1997, pp. 780–785.Google Scholar