Real-time Object Tracking with Active PTZ Camera using Hardware Acceleration Approach

Автор: Sanjay Singh, Ravi Saini, Sumeet Saurav, Anil K Saini

Журнал: International Journal of Image, Graphics and Signal Processing(IJIGSP) @ijigsp

Статья в выпуске: 2 vol.9, 2017 года.

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This paper presents the design and implementation of a dedicated hardware (VLSI) architecture for real-time object tracking. In order to realize the complete system, the designed VLSI architecture has been integrated with different input/output video interfaces. These video interfaces along with the designed object tracking VLSI architecture have been coded using VHDL, simulated using ModelSim, and synthesized using Xilinx ISE tool chain. A working prototype of complete object tracking system has been implemented on Xilinx ML510 (Virtex-5 FX130T) FPGA board. The implemented system is capable of tracking the moving target object in real-time in PAL (720x576) resolution live video stream directly coming from the camera. Additionally, the implemented system also provides the real-time desired camera movement to follow the tracked object over a larger area.

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VLSI Architecture, Real-time Object Tracking, FPGA Implementation

Короткий адрес: https://sciup.org/15014166

IDR: 15014166

Список литературы Real-time Object Tracking with Active PTZ Camera using Hardware Acceleration Approach

  • I. Haritaoglu, D. Harwood, and L.S. Davis, W4: Real-time Surveillance of People and Their Activities, IEEE Transsaction on Pattern Analysis and Machine Intelligence, Vol. 22, No. 8, pp. 809-830, 2000.
  • X. Chen and J. Yang, Towards Monitoring Human Activities Using an Omni-directional Camera, In Proceedings: Fourth IEEE International Conference on Multimodal Interfaces, pp. 423-428, 2002.
  • C.R. Wren, A. Azarbayejani, T. Darrell, and A.P. Pentland, Pfinder: Real-Time Tracking of the Human Body, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, No. 7, pp. 780-785, 1997.
  • S.S. Intille, J.W. Davis, and A.E. Bobick, Real-Time Closed-World Tracking, In Proceedings: IEEE Conference on Computer Vision and Pattern Recognition, pp. 697-703, 1997.
  • B. Coifmana, D. Beymerb, P. McLauchlanb, and J. Malikb, A Real-Time Computer Vision System for Vehicle Tracking and Traffic Surveillance, Transportation Research Part C: Emerging Technologies, Vol.6, No. 4, pp. 271–288, 1998.
  • S. Paschalakis, and M. Bober, Real-Time Face Detection and Tracking for Mobile Videoconferencing, Real-Time Imaging, Vol. 10, No. 2, pp. 81–94, 2004
  • T. Sikora, The MPEG-4 Video Standard Verification Model, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 7, No. 1, pp. 19-31, 1997.
  • A. Eleftheriadis and A. Jacquinb, Automatic Face Location Detection snd Tracking for Model-Assisted Coding of Video Teleconferencing Sequences at Low Bit-Rates, Signal Processing: Image Communication, Vol. 7, No. 3, pp. 231–248, 1995.
  • Yilmaz, O. Javed, and M. Shah, Object Tracking: A Survey, ACM Computing Surveys, Vol. 38, No. 4, Article 13, pp. 1-45, 2006.
  • X. Li, W. Hu, C. Shen, Z. Zhang, A. Dick, and V.D. Hengel, "A Survey of Appearance Models in Visual Object Tracking, ACM Transactions on Intelligent Systems and Technology, Vol. 4, No. 4, Article 58, pp. 1-48, 2013.
  • F. Porikli, Achieving Real-time Object Detection and Tracking under Extreme Condition, Journal of Real-time Image Processing, Vol. 1, No. 1, pp. 33-40, 2006.
  • A. Doulamis, N. Doulamis, K. Ntalianis, and S. Kollias, An Efficient Fully Unsupervised Video Object Segmentation Scheme Using an Adaptive Neural-Network Classifier Architecture, IEEE Transactions on Neural Networks, Vol. 14, No. 3, pp. 616-630, 2003.
  • J. Ahmed, M.N. Jafri, J. Ahmad, and M.I. Khan, Design and Implementation of a Neural Network for Real-Time Object Tracking, International Journal of Computer, Information, Systems and Control Engineering, Vol. 1, No. 6, pp. 1825-1828, 2007.
  • J. Ahmed, M.N. Jafri, and J. Ahmad, Target Tracking in an Image Sequence Using Wavelet Features and a Neural Network, In Proceedings: IEEE Region 10 TENCON 2005 Conference, pp. 1-6, 2005.
  • C. Stauffer and W. Grimson, Learning Patterns of Activity using Real-time Tracking, IEEE Transactions On Pattern Analysis and Machine Intelligence, Vol. 22, No. 8, pp. 747-757, 2000.
  • C. Kim and J. N. Hwang, Fast and Automatic Video Object Segmentation and Tracking for Content-Based Applications, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 12, No. 2, pp. 122-129, 2002.
  • T. Gevers, Robust Segmentation and Tracking of Colored Objects in Video, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 14, No. 6, pp. 776-781, 2004.
  • C.E. Erdem, Video Object Segmentation and Tracking using Region-based Statistics, Signal Processing: Image Communication, Vol. 22, No. 10, pp. 891-905, 2007.
  • K.E. Papoutsakis and A.A. Argyros, Object Tracking and Segmentation in a Closed Loop, Advances in Visual Computing: Lecture Notes in Computer Science, Vol. 6453, pp. 405-416, 2010.
  • F. Kristensen, H. Hedberg, H. Jiang, P. Nilsson, and V.O. Wall, An Embedded Real-Time Surveillance System: Implementation and Evaluation, Journal of Signal Processing Systems, Vol. 52, No. 1, pp. 75-94, 2008.
  • M. Isard and A. Blake, CONDENSATION – Conditional Density Propagation for Visual Tracking, International Journal of Computer Vision, Vol. 29, No. 1, pp. 5 - 28, 1998.
  • F. Porikli, O. Tuzel, and P. Meer, Covariance Tracking using Model Update Based on Lie Algebra, In Proceedings: IEEE Conference on Computer Vision and Pattern Recognition, pp. 728-735, 2006.
  • S. Wong, Advanced Correlation Tracking of Objects in Cluttered Imagery: In Proceeding: SPIE, Vol. 5810, pp. 1-12, 2005.
  • A. Yilmaz, X. Li, and M. Shah, Contour-based Object Tracking with Occlusion Handling in Video Acquired using Mobile Cameras, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 11, pp. 1531-1536, 2004.
  • M. Kass, A. Witkin, and D. Terzopoulos, Snakes: Active Contour Models, International Journal of Computer Vision, Vol. 1, No. 4, pp 321-331, 1988.
  • M. J. Black and A. D. Jepson, EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-based Representation, International Journal of Computer Vision, vol. 26, no. 1, pp. 63 - 84, 1998.
  • C.M. Li, Y.S. Li, Q.D. Zhuang, Q.M. Li, R.H. Wu, and Y. Li, Moving Object Segmentation and Tracking In Video, In Proceedings: Fourth International Conference on Machine Learning and Cybernetics, pp. 4957-4960, 2005.
  • D. Comaniciu, R. Visvanathan, and P. Meer, Kernel based Object Tracking, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 25, No. 5, pp. 564-577, 2003.
  • D. Comaniciu, V. Ramesh, P. Meer, Real-time Tracking of Non-Rigid Objects Using Mean Shift, In Proceedings: IEEE Conference on Computer Vision and Pattern Recognition, Vol. 2, pp. 142–149, 2000.
  • V.P. Namboodiri, A. Ghorawat, and S. Chaudhuri, Improved Kernel-Based Object Tracking Under Occluded Scenarios, Computer Vision, Graphics and Image Processing: Lecture Notes in Computer Science, Vol. 4338, pp. 504-515, 2006.
  • A. Dargazany, A. Soleimani, and A. Ahmadyfard, Multibandwidth Kernel-Based Object Tracking, Advances in Artificial Intelligence, Vol. 2010, Article ID 175603, pp. 1-15, 2010.
  • M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking, IEEE Transactions on Signal Processing, Vol. 50, No. 2, pp. 174-188, 2002.
  • F. Gustafsson, F. Gunnarsson, N. Bergman, U. Forssell, J. Jansson, R. Karlsson, and P.J. Nordlund, Particle Filters for Positioning, Navigation, and Tracking, IEEE Transactions on Signal Processing, Vol. 50, No. 2, pp. 425-237, 2002.
  • P. Pérez, C. Hue, J. Vermaak, and M. Gangnet, Color-Based Probabilistic Tracking, Computer Vision: Lecture Notes in Computer Science, Vol. 2350, pp. 661-675, 2002.
  • S. Agrawal, P. Engineer, R. Velmurugan, and S. Patkar, FPGA Implementation of Particle Filter based Object Tracking in Video, In Proceedings: International Symposium on Electronic System Design, pp. 82-86, 2012.
  • J.U. Cho, S.H. Jin, X.D. Pham, D. Kim, and J.W. Jeon, A Real-Time Color Feature Tracking System Using Color Histograms, In Proceedings: International Conference on Control, Automation and Systems, pp. 1163-1167, 2007.
  • J.U. Cho, S.H. Jin, X.D. Pham, D. Kim, and J.W. Jeon, FPGA-Based Real-Time Visual Tracking System Using Adaptive Color Histograms, In Proceedings: IEEE International Conference on Robotics and Biomimetics, pp. 172-177, 2007.
  • J. Xu, Y. Dou, J. Li, X. Zhou, and Q. Dou, FPGA Accelerating Algorithms of Active Shape Model in People Tracking Applications, In Proceedings: 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools, pp. 432-435, 2007.
  • M. Shahzada and S. Zahidb, Image Coprocessor: A Real-time Approach towards Object Tracking, In Proceedings: International Conference on Digital Image Processing, pp. 220-224, 2009.
  • K.S. Raju, G. Baruah, M. Rajesham, P. Phukan, and M. Pandey, Implementation of Moving Object Tracking using EDK, International Journal of Computer Science Issues, Vol. 9, No. 3, pp. 43-50, 2012.
  • K.S. Raju, D. Borgohain, and M. Pandey, A Hardware Implementation to Compute Displacement of Moving Object in a Real Time Video, International Journal of Computer Applications Vol. 69, No. 18, pp. 41-44, 2013.
  • M. McErlean, An FPGA Implementation of Hierarchical Motion Estimation for Embedded Object Tracking, In Proceedings: IEEE International Symposium on Signal Processing and Information Technology, pp. 242-247, 2006.
  • Y.P. Hsu, H.C. Miao, and C.C. Tsai, FPGA Implementation of a Real-Time Image Tracking System, In Proceedings: SICE Annual Conference, pp. 2878 - 2884, 2010.
  • L.N. Elkhatib, F.A. Hussin, L. Xia, and P. Sebastian, An Optimal Design of Moving Object Tracking Algorithm on FPGA, In Proceedings: International Conference on Intelligent and Advanced Systems, pp. 745 - 749, 2012.
  • S. Wong and J. Collins, A Proposed FPGA Architecture for Real-Time Object Tracking using Commodity Sensors, In Proceedings: 19th International Conference on Mechatronics and Machine Vision in Practice, pp. 156-161, 2012.
  • D. Popescu and D. Patarniche, FPGA Implementation of Video Processing-Based Algorithm for Object Tracking, U.P.B. Sci. Bull., Series C, Vol. 72, No. 3, pp. 121-130, 2010.
  • S. Kang, J.K. Paik, A. Koschan, B.R. Abidi, M.A. andAbidi, Real-time video tracking using PTZ cameras, In Proceedings: SPIE, Volume 5132, pp. 103-111, 2003.
  • T. Dinh, Q. Yu, and G. Medioni, Real Time Tracking using an Active Pan-Tilt-Zoom Network Camera, In Proceedings: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3786-3793, 2009.
  • P.D.Z. Varcheie and G.A. Bilodea, Active People Tracking by a PTZ Camera in IP Surveillance System, In Proceedings: IEEE International Workshop on Robotic and Sensors Environments, pp. 98 – 103, 2009.
  • M.A. Haj, A.D. Bagdanov, J. Gonzalez, and F.X. Roca, Reactive object tracking with a single PTZ camera, In Proceedings: International Conference on Pattern Recognition, pp. 1690-1693, 2010.
  • S.G. Lee and R. Batkhishig, Implementation of a Real-Time Image Object Tracking System for PTZ Cameras, Convergence and Hybrid Information Technology: Communications in Computer and Information Science, Vol. 206, pp 121-128, 2011.
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