Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/8930
標題: 適用於H.264/AVC編碼器之基於移動向量物件追蹤電路架構設計與實現
VLSI Architecture Design of Object Tracking Based on Motion Vectors in H.264/AVC Video Encoder
作者: 黃唯竣
Huang, Wei-Chun
關鍵字: H.264;H.264;Motion Vector;Object Tracking;移動向量;物件追蹤
出版社: 電機工程學系所
引用: [1] Advanced video coding for generic audiovisual services, Recommendation ITU-T H.264, March 2009. [2] Rob Koenen, “Overview of the MPEG-4 Standard,” Moving Picture Experts Group, March 2002. [3] Video Codec for Audiovisual Services at px64 kbits, ITU-T Recommendation H.261. pp. 4-5. March 1993. [4] T. Koga, K. Iinuma, A. Hirano, Y. Iijima, and T. Ishiguro, “Motion compensated interframe coding for video conferencing,” Proceedings of National Telecommunications Conference, pp. G5.3.1-5.3.5, November 1981. [5] J. Y. Tham, S. Ranganath, M. Ranganath, and A. A. Kassim, “A novel unrest-recited center-biased diamond search algorithm for block motion estimation,” IEEE Trans. Circuits Syst. Video Technol., Volume 8, Number 4, pp. 369-378. August 1998. [6] S. Zhu and K. K. Ma, “A new diamond search algorithm for fast block-matching motion estimation,” IEEE Trans. Image Process., Volume 9, pp. 287-290, February 2000. [7] L. M. Po and W. C. Ma, “A novel four-step search algorithm for fast block estimation,” IEEE Trans. Circuits Syst. Video Technol., Volume 6, Number 3, pp. 313-317, January 1996. [8] A. Zaccarin and B. Liu, “Fast algorithms for block motion estimation,” Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Number 3, pp. 449-452, 1992. [9] W. Li and E. Salari, “Successive elimination algorithm for motion estimation,” IEEE Trans. Image Process., Volume 4, pp. 105-107. January 1995. [10] X. Q. Gao, C. J. Duanmu, and C. R. Zou, “A multilevel successive elimination algorithm for block matching motion estimation,” IEEE Trans. Image Process., Volume 9, pp. 501-504, March 2000. [11] M. Brünig and W. Niehsen, “Fast full-search block matching,” IEEE Trans. Circuits Syst. for Video Technol., Volume 11, pp. 241-247, February 2001. [12] Y. W. Huang, S. Y. Chien, B. Y. Hsieh, and L. G. Chen, “Global elimination algorithm and architecture design for fast block matching motion estimation,” IEEE Trans. Circuits Syst. Video Technol.. Volume 14, pp. 898-907. 2004. [13] T. Wiegand, X. Zhang, and B. Girod, “Long-term memory motion-compensated prediction,” IEEE Trans. Circuits Syst. Video Technol., Volume 9, pp. 70-84, February 1999. [14] S. Wenger, “H.264/AVC over IP,” IEEE Trans. Circuits Syst. Video Technol., Volume 13, pp. 645-656, July 2003. [15] T. Wedi, “Motion compensation in H.264/AVC,” IEEE Trans. Circuits Syst. Video Technol., Volume 13, pp. 577-586, July 2003. [16] D. Marpe, H. Schwarz, and T. Wiegand, “Context-adaptive binary arithmetic coding in the H.264/AVC video compression standard,” IEEE Trans. Circuits Syst. for Video Technol., Volume 13, pp. 620-636. July 2003. [17] Y. W. Huang, B. Y. Hsieh, T. C. Wang, S. Y. Chien, S. Y. Ma, C. F. Shen, and L. G. Chen, “Analysis and reduction of reference frames for motion estimation in MPEG-4 AVC/JVT/H.264,” Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, April 2003. [18] Y. Su and M. T. Sun, “Fast multiple reference frame motion estimation for H.264,” Proceedings of IEEE International Conference on Multimedia and Exposition 2004, Volume 1, pp. 695-698, June 2004. [19] Joint Video Team of ISO/IEC MEPG and ITU-T VCEG, H.264/AVC Reference Software JM14.2, http://bs.hhi.de/suehringg/tml/dwnload/ [20] Gonzalez and Woods, Digital Image Processing, third edition, Pearson Education Inc, 2008. [21] C. Regazzoni, V. Ramesh, and G. L. Foresti, “Scanning the issue/technology,” Proceedings of the IEEE, volume 89, number 10, pp. 1355-1367, Oct. 2001. [22] LIU Zhi-fang and YOU Zhisheng, “A Real-time Vision-based Vehicle Tracking and Traffic Surveillance,” IEEE Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. [23] W. H. Wang, “Automatic Tracking Object Surveillance System,” Thesis, National Chung Hsing, 2006. [24] S. Y. Chien, Video segmentation: algorithms, hardware architectures, and applications, Ph. D. Dissertation, National Taiwan University, May 2003. [25] “Embedded Pentium® Processor with MMX™ Technology,” ©Intel Corporation, 1998. [26] Y. K. Lai, and Y. C. Chung, “An Object Tracking Processor Core for Intelligent Surveillance System-on-Chip Applications,” Proceedings of International Conference on Solid State Devices and Materials (SSDM), September 2007. [27] Yu-Wen Huang, Bing-Yu Hsieh, Shao-Yi Chien, and Liang-Gee Chen, “Simple and effective algorithm for automatic tracking of a single object using a pan-tilt-zoom camera,” in Proceedings of 2002 IEEE International Conference on Multimedia and Expo (ICME 2002), Lausanne, Switzerland, August 2002. [28] Mansour A Al Zuair, and Bandar Al Rashed, “Tracking Using Motion Estimation,” IEEE Proceedings of the International Conference on Computer and Communication Engineering 2008, pp.393-395, 2008. [29] R. Fisher, S. Perkins, A. Walker and E. Wolfart, “Spatial Filters - Gaussian Smoothing,” 2003, http://homepages.inf.ed.ac.uk/rbf/HIPR2/gsmooth.htm [30] C. C. Liang, “Architecture and Algorithm Design of High-resolution Real-time Video Object Segmentation,” Thesis, National Taiwan University, pp.30-42, June 2008. [31] Takanori Yokoyama, Toshiki Iwasaki, and Toshinori Watanabe, “Motion Vector Based Moving Object Detection and Tracking in the MPEG Compressed Domain,” IEEE 2009 Seventh International Workshop on Content-Based Multimedia Indexing, pp.201-206, 2009. [32] Azzam Sleit, Imad Salah, and Rahmeh Jabay, “Approximating Images Using Minimum Bounding Rectangles,” Proceedings of IEEE Conference of Applications of Digital Information and Web Technologies (ICADIWT) 2008, pp.394-396, 2008. [33] Bashar M. A. Ahmad, “A Novel Texture & Spatial based Framework for Motion Vectors Enhancement in Compressed Domain,” Thesis, National Chiao Tung University, pp.22-35, June 2004. [34] Ashraf M. A. Ahmad, “Study on Motion Vector Refinement in Video Processing and Transcoding Applications,” Dissertation, National Chiao Tung University, pp.21-40, June 2006. [35] John L. Smith, “Implementing Median Filter in XC4000E FPGAs,” Design Hints and Issues, Xilinx, pp.16. [36] “DW_div Combinational Divider,” DesignWare Foundation Building Block, Synopsys Inc, March 2010.
摘要: 
監視系統已經是今日生活不可或缺的一部分。一個典型的監視系統包含有錄影功能和物件追蹤能力。錄影功能將影像進行編碼且保存在儲存媒體內,以便日後追蹤過去發生的事件。物件追蹤能力使系統可以察覺不正常的事件發生以及入侵者,並且及時通知警衛採取行動。也因此可以避免他人的惡意造成傷亡及損失。

雖然市面上已經有許多的監視系統,然而兩個主要元件:影像壓縮及物件追蹤並無法共享系統資源,造成系統資源的浪費以及建置的成本增加。

本文提出了一種使用移動估測結果來進行物件追蹤的電路架構。演算法由前置濾波器、改良式橫山向量特徵畫面、以及區塊為基礎的物件追蹤方法組成。這個架構可以使用H.264編碼器來實現物件追蹤。在電路架構方面,相較於背景註冊方式,此架構節省了約略91%的記憶體使用量。在使用90奈米製程系統晶片製程的情況下,可以執行CIF、VGA、720p、1080p解析度畫面即時物件追蹤運算。此種只需要極低運算量及極少儲存空間的架構可以廣泛的使用在許多應用層面。

Surveillance system is widely used today. A typical surveillance system includes video recording function and object tracking ability. Video recording function encodes the video and stores it in the storage media. The recorder is used for one to track the affairs happened in the past. Object tracking ability makes the system aware the abnormal affairs and intruders and notice the guards to take immediate action. It can also avoid damage due to inattention of people.

Although various kinds of surveillance systems have been produced, the two main functions, video compression and object tracking, operate independently and cannot share the resource with each other. This design method will waste the resource and increase the cost.

In this thesis, architecture of object tracking using motion estimation results is proposed. The algorithm is a combination of preprocessing noise filter, modified Yokoyama's vector featured image, and block based object tracking. It can perform the object tracking and shares the resource with the H.264 encoder. In hardware implementation, approximate 91% memory usage is saved than background registration. It can perform object tracking for CIF, VGA, 720p, and 1080p resolutions by using 90nm process with system-on-chip design in real-time. The architecture with fewer computation and lower necessary storage capacity can be easily applied to various applications.
URI: http://hdl.handle.net/11455/8930
其他識別: U0005-2308201022065600
Appears in Collections:電機工程學系所

Show full item record
 

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.