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一种复杂环境下运动目标检测的背景构建方法

Background Building Method of Moving Objects Detection in Complex Scenes
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摘要 针对复杂环境下背景构建困难等问题,提出了一种彩色图像依照目标运动状态实时进行更新的背景构建方法。该方法通过定义彩色图像距离,根据当前图像与背景图像之间的距离变化定义运动状态矩阵,从而利用状态矩阵结合当前帧图像的彩色特征更新背景。该方法无需假设背景模型,能够适应各类复杂的突变,通过获取包含多类目标的实测彩色图像实验验证了算法的有效性和准确性。 We present a background image building method to deal with the problem of color images motion object detection in real-time.The distance between color images is defined to compare the frame image and the background image according to the frame sequences.The motion state matrix is extracted to update background image in pixels level.The method need not background models and fit variety changes.Actual color images were used to test the method.The experimental results show that our method is effective and accurate.
出处 《武汉大学学报(信息科学版)》 EI CSCD 北大核心 2010年第8期963-966,共4页 Geomatics and Information Science of Wuhan University
基金 国家自然科学基金资助项目(60541001) 全国优秀博士学位论文作者专项基金资助项目(200443) “泰山学者”建设工程专项经费资助项目 山东省高校优秀青年教师国内访问学者基金资助项目
关键词 运动目标检测 背景差 运动状态矩阵 更新 motion object detection background subtraction motion state matrix update
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参考文献8

  • 1Stauffer C, Grimson E. Learning Patterns of Activity Using Real-time tracking[J].IEEE Transactions on Pattern Recognition and Machine Intelligence, 2000, 22(8) :747-757.
  • 2Stauffer C, Grimson W E I.. Adaptive Background Mixture Models for Real time Tracking [J]. Computer Vision and Pattern Recognition, 1999 (2): 246-252.
  • 3Elgammal A, Harwood D, Davis L. Non-parametric Model for Background Subtraction [C]. The IEEE International Conference on Computer Vision Frame-Rate Workshop, Kerkyra, Greece, 1999.
  • 4Liu Z, Wang X Y. Segmenting Foreground from Similarly Colored Background[J]. Optical Engineering. 2008,47(7): 1-11.
  • 5Cuechiara R, Grana C, Piccardi M. Detecting Moving Objects, Ghosts and Shadows in Video Streams [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003,25(10):1 337-1 342.
  • 6Cucchiara R, Grana C, Piccardi M, et al. Detecting Objects, Shadows and Ghosts in Video Streams by Exploiting Color and Motion Information[C]. IEEE International Conference on Image Analysis and Processing, Palermo, Italy, 2001.
  • 7Tian Y L, Lu M, Hampapur A. Robust and Effi- cient Foreground Analysis for Real-time Video Surveillance[C]. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, CA, USA, 2005.
  • 8Hansung K, Ryuuki S, Itaru K. Robust Foreground Extraction Technique Using Background Subtraction with Multiple Thresholds[J]. Optical Engineering, 2007,46(9) : 1-12.

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