期刊文献+

快速背景提取及更新算法 被引量:4

Rapid Background Extraction and Update Algorithm
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摘要 定点DSP浮点运算效率低、存储空间有限,应用传统的背景提取与更新算法时,检测速度慢、实时性差。针对该问题,利用相邻视频帧的时间相关性,根据背景像素灰度以最大概率出现在视频序列中的假设,提取初始背景参考帧。在背景更新环节,对原始背景与当前图像像素赋予不同的权值,并且基于移位运算得到新的背景。在TMS320DM642定点DSP上所做的实验表明,该算法可以满足帧率为25FPS下的实时应用。 If using the traditional algorithms of background extraction and update on the fixed-point DSP, which is memory-limited and weak at floating-point operation, the detection speed is slow and the real-time ability is poor. The algorithm initializes the background reference frame according to the hypothesis that the background pixel intensity appears in video sequence with maximum probability and the temporal relativity between two neighboring frames. In the session of background update, the algorithm updates the background reference frame by assigning different weights to the original background and the current frame and calculating the result based on shifting operation. It is successfully implemented on TMS320DM642 and results show that the algorithm can meet the real-time constraint in 25 FPS.
出处 《计算机工程》 CAS CSCD 北大核心 2010年第3期283-284,F0003,共3页 Computer Engineering
基金 国家自然科学基金资助项目(60503027) 国家创新研究群体科学基金资助项目(60721062) 浙江省科技厅基金资助项目(2007C1046)
关键词 背景提取及更新 定点DSP 实时性 background extraction and update fixed-point DSP real-time ability
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参考文献4

  • 1Fujiyoshi H, Lipton A. Real-time Human Motion Analysis by Image Skeletonization[C]//Proc. of WACV'98. Princeton, USA: [s. n.], 1998: 15-21.
  • 2Picardi M. Background Subtraction Techniques: A Review[C]//Proc. of IEEE International Conference on Systems, Man and Cybernetics. Hague, Holland: [s. n.], 2004: 3099-3104.
  • 3Collins R, Lipton A, Kanade T, et al. A System for Video Surveillance and Monitoring[R]. Robotics Institute, Carnegie Mellon University, Tech. Rep.: CMU-RI-TR-00-12, 2000.
  • 4侯志强,韩崇昭.基于像素灰度归类的背景重构算法[J].软件学报,2005,16(9):1568-1576. 被引量:97

二级参考文献25

  • 1Horn BK, Schunk BG. Determining optical flow. Artificial Intelligence, 1981,17(1-3): 185-203.
  • 2Smith SM, Brady JM. ASSET-2: Real-Time motion segmentation and shape tracking. IEEE Trans. on PAMI, 1995,17(8):814-820.
  • 3Neff A, Colonnese S, Russo G, Talone P. Automatic moving object and background separation. Signal Processing, 1998,66(2):219-232.
  • 4Meier T, Ngan KN. Automatic segmentation of moving objects for video object plane generation. IEEE Trans. on Circuits and Systems for Video Technology, 1998,8(5):525-538.
  • 5Jolly MPD, Lakshmanan S, Jain AK. Vehicle segmentation and classification using deformable templates. IEEE Trans. on PAMI,1996,18(3):293-308.
  • 6Ridder C, Munkelt O, Kirchner H. Adaptive background estimation and foreground detection using Kalman-filter. In: Proc. of the Int'l Conf. on Recent Advances in Mechatronics, ICRAM'95. UNESCO Chair on Mechatronics, 1995. 193-199.
  • 7Friedman N, Russell S. Image segmentation in video sequences: A probabilistic approach. In: Proc. of the 13th Conf. on Uncertainty in Artificial Intelligence (UAI). San Francisco, 1997.
  • 8Stauffer C, Grimson WEL. Adaptive background mixture models for real-time tracking. In: Proc. of the IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, Vol 2. 1999. 246-252.
  • 9KaewTraKulPong P, Bowden R. An improved adaptive background mixture model for real-time tracking with shadow detection. In:The 2rid European Workshop on Advanced Video-based Surveillance Systems. Kingston upon Thames, 2001.
  • 10Elgammal A, Harwood D, Davis L. Non-Parametric model for background subtraction. In: Proc. of the 6th European Conf. on Computer Vision. Dublin Ireland, 2000.

共引文献96

同被引文献31

  • 1董士崇,王天珍,许刚.视频图像中的运动检测[J].武汉理工大学学报(信息与管理工程版),2004,26(4):1-3. 被引量:22
  • 2侯志强,韩崇昭.基于像素灰度归类的背景重构算法[J].软件学报,2005,16(9):1568-1576. 被引量:97
  • 3魏志强,纪筱鹏,冯业伟.基于自适应背景图像更新的运动目标检测方法[J].电子学报,2005,33(12):2261-2264. 被引量:54
  • 4陈振华,周锐锐,李光伟,毕笃彦.一种改进的高斯混合背景模型算法及仿真[J].计算机仿真,2007,24(11):190-193. 被引量:16
  • 5Fejes S,Davis L S. What can projections of flow fields tell us about the visual motion[A].Bombay,India,1998.979-986.
  • 6Meier T,Ngan KN. Automatic segmentation of moving objects for video object plane generation[J].IEEE Transactions on Circuits and Systems for Video Technology,1998,(05):525-538.doi:10.1109/76.718500.
  • 7Ridder C,Munkelt O,Kirchner H. Adaptive background estimation and foreground detection using Kahnan-fiher[A].1995.193-199.
  • 8Gali~ S, Lor~ari~ S. Spatio-temporal image se~nentation using op- tical flow and clustering algorithm [ C ]//Proceedings of the First International Workshop on Image and Signal Processing and Analy- sis, Piscataway,N.l: IEEE, 2000:63-68.
  • 9Stauffer C, Grim.son W E L. Adaptive background mixture models for real-time tracking[ C ]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Piscataway, NJ : IEEE, 1999:246 - 252.
  • 10Zivkovie Z. Improved adaptive Gaussian mixture model for back-ground subtraction[ C]// IEEE Proceedings of the 17th Interna- tional Conference on Pattern Recognition, Piscataway, NJ : IEEE, 2004:28 -31.

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