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基于演算侧抑制模型的运动目标检测方法

Moving Object Detection Based on Algorithmic Lateral Inhibition
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摘要 研究了一种新的基于时空信息的运动目标检测方法.引入了多通道的概念,采用演算侧抑制模型ALI进行运动目标检测.首先根据时域信息创建多个图像处理通道,将视频图像在各通道上分别进行时域ALI、时空域ALI运算获取运动信息,然后将各通道运动信息进行融合提取运动目标,并用时空域ALI消除噪声.仿真实验表明,该方法在复杂背景下可以精确获取运动目标的轮廓. A new method based on spatial-temporal information for the task of moving objects has been introduced. The algorithmic lateral inhibition model （ALI） is proposed to extract the multiple channels in the form of temporal and spatial-temporal filtering. Then the noise is dilut spatial-temporal ALl. The experimental results show that the approach can obtain the silhouettes accurately under complex environment.
作者 祝红芳 杜红伟 王从庆
机构地区 南京航空航天大学自动化学院 江西工业职业技术学院
出处 《湘潭大学自然科学学报》 CAS CSCD 北大核心 2009年第3期143-147,共5页 Natural Science Journal of Xiangtan University
关键词 时空信息 演算侧抑制模型 运动目标检测 spatial-temporal information ALL moving object detection detection motion in ed by the of objects
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献7

  • 1印勇,王亚飞.基于空间邻域相关性的运动目标检测方法[J].光电工程,2009,36(2):1-5. 被引量：17
  • 2JOSE M,ANA E D ,ANTONIO F C,et al. Knowledge modelling for the motion detection task:the algorithmic lateral inhibition method[J]. Expert Systems with Applications, 2004,27 : 169-- 185.
  • 3MARI'AT L, FERNA' NDEZ--CABALLERO A, MIRA J, et al. Algorithmic lateral inhibition method in dynamic and selective vishal attention task : Application to moving objects detection and labelling[J]. Expert Systems with Applications, 2006,31:570--594.
  • 4FERNA' NDEZ-- CABALLERO A, MIRA J, DELGDO E, et al. Lateral interaction in accumulative computation : a model for motion detection[J]. Neuroeomputing,2003,50 :314-- 364.
  • 5FERNA' NDEZ--CABALLERO A, MIRA J, FERNA' NDEZ M A, et al. Segmentation from motion of non--rigid objects by neuronal lateral interaction[J]. Pattern Recognition Letters, 2001,22 :1 517-- 1 524.
  • 6FERNA'NDEZ--CABALLERO A,FERNA'NDEZ M A,MIRA J,et al. Spatio--temporal shape building from image sequences using lateral interaction in accumulative computation[J]. Pattern Recognition, 2003,36:1 131--1 142.
  • 7陈卉,欧阳楷.用于图象增强的侧抑制网络模型的仿真比较[J].系统仿真学报,2003,15(1):100-103. 被引量：15

二级参考文献14

  • 1于跃龙,卢焕章.基于背景构造的视频对象分割技术[J].计算机工程与科学,2006,28(1):36-38. 被引量：4
  • 2郭永涛,宋焕生,贺昱曜.视频交通监控系统中背景提取算法[J].电视技术,2006,30(5):91-93. 被引量：15
  • 3Ridder Christof, Olaf Munkelt, Harald Kirchner. Adaptive Background Estimation and Foreground Detection using Kalman-Filtering [C]// Proceedings of the International Conference on recent Advances in Meehatronies, Istanbul, Turkey, August 14-16, 1995. Istanbul, Turkey: UNESCO Chair on Mechatronics, 1995: 193-199.
  • 4Richard Wren Christopher, Azarbayejani All, Darrell Trevor, et al. Pfmder: Real-Time Tracking of the Human Body [J]. IEEE Transactions on Pattern, Analysis and Machine Intelligence, 1997, 19(7): 780-785.
  • 5Stauffer Chris, Grimson W E L. Adaptive background mixture models for real-time tracking [C]// Proceeding of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Fort Collins, CO, USA, June 23-25, 1999. Washington DC: IEEE, 1999, 2: 245-252.
  • 6Elgammal Ahmed M, Harwood David, Davis Larry S. Non-parametric model for background subtraction [C]// Proceedings of the 6th European Conference on Computer Vision, Dublin, Ireland, June 26 -July 1, 2000. London, UK: Springer-Verlag, 2000: 751-767.
  • 7Rittscher J, Kato J, Joga S, et al. A probabilistic background model for tracking [C]// Proceedings of the 6th European Conference on Computer Vision, Dublin, ' Ireland, June 26 -July 1, 2000. London, UK: Springer-Verlag, 2000: 336-350.
  • 8Yang Sheng-Yan, Hsu Chiou-Ting. Background Modeling from GMM Likelihood Combined with Spatial and Color Coherency [C]//IEEE Internalional Conference on Image Processing, Atlanta, GA, Oct 8-11, 2006. Washington D C: IEEE, 2006: 2801-2804.
  • 9Seki Makito, Toshikazu Wada, Hideto Fujiwara, et al. Background subtraction based on cooccurrence of image variations [J]. Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (S1063-6919), 2003, 2: 65-72.
  • 10Aach Til, Andre Kaup. Bayesian Algorithms for Adaptive Change Detection in Image Sequences Using Markov Random Fields [J]. Signal Proeessing: Image Communication(S0923-5965), 1995, 7(2): 147-160.

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湘潭大学自然科学学报
2009年 第3期

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