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融合时空信息的前景／阴影视频分割算法 被引量：3

A Spatiotemporal Algorithm for Video Foreground and Shadow Segmentation
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摘要 视频目标分割是视频目标跟踪、统计以及识别的基础.阴影是影响目标分割准确性的重要因素,有效对阴影进行检测与消除可提高视频目标分割的质量.本文提出一种采用状态机对阴影进行建模的方法,通过阴影模型来消除阴影.算法定义背景、阴影以及前景的势函数,利用马尔可夫随机场融合视频序列的时空邻域信息,采用Gibbs 采样算法求解最大后验概率,提高视频目标分割的质量.在不同环境下对本文算法的有效性进行测试,并与其他算法进行比较,结果证明本文算法的有效性. Video segmentation is important for video object tracking, counting and recognition. Shadows are the factors that affect the accuracy of object segmentation. Efficiently detecting and removing the shadows can improve the quality of object segmentation. An algorithm for ,video-foreground and shadow segmentation is proposed in this paper. It models shadows with state machine and the shadows are removed according to the shadow models. The potential functions for the background, shadow and foreground are defined. The spatiotemporal neighboring relationships in the video sequence are constructed by using Markov random fields. Gibbs sampling algorithm is adopted to solve the MAP problem and thus the segmentation qualityis improved . The correctness of the proposed algorithm is tested under different environments and the results demonstrate the validity of the algorithm compared with other algorithms.
作者 褚一平 叶修梓 黄叶珏 张引 张三元
机构地区 浙江大学计算机科学与技术学院CAD＆CG国家重点实验室 杭州电子科技大学计算机学院 浙江工业职业技术学院计算机系
出处 《模式识别与人工智能》 EI CSCD 北大核心 2008年第4期546-551,共6页 Pattern Recognition and Artificial Intelligence
基金 国家自然科学基金项目(No.60473106) 国家教育部博士点基金项目(No.20060335114) 长江学者和创新团队发展计划项目(No.IRT0652)资助
关键词 视频目标分割 阴影检测与消除 时空邻域关系 马尔可夫随机场(MRF) Video Object Segmentation, Shadow Detection and Elimination, SpatiotemporalNeighboring Relationship, Markov Random Field （MRF）
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献13

  • 1Yang Tao, Pan Quan, Li S Z, et al. Multiple Layer Based Background Maintenance in Complex Environment//Proc of the 3rd International Conference on Image and Graphics. Hong Kong, China, 2004- 112-115
  • 2Yang Tao, Li S Z, Pan Quan, et al. Real-Time Multiple Object Tracking with Occlusion Handling in Dynamic Scenes// Proc of the IEEE Computer Society Conference on Computer Vision and Pattern Reeognition. San Diego, USA, 2005, Ⅰ: 970- 975
  • 3Zivkovic Z. Improved Adaptive Gaussian Mixture Model for Background Subtraction// Proc of the 17th International Conference on Pattern Recognition, Cambridge, UK, 2004, Ⅱ: 28 -31
  • 4Stauffer C, Grimson W E L. Learning Patterns of Activity Using Real-Time Tracking, IEEE Trans on Pattern Analysis and Machine Intelligence, 2000, 22(8): 747-757
  • 5Elgammal A, Duraiswami R, Harwood D, et al. Background and Foreground Modeling Using Nonparametric Kernel Density Estimation for Visual Surveillance. Proc of the IEEE, 2002, 90 ( 7 ) 1151 - 1163
  • 6陈睿,邓宇,向世明,李华.结合强度和边界信息的非参数前景/背景分割方法[J].计算机辅助设计与图形学学报,2005,17(6):1278-1284. 被引量：13
  • 7Zhou Yue, Gong Yihong, Hai Tai. Background Modeling Using Time Dependent Markov Random Field with Image Pyramid [ EB/ OL]. [ 2005 - 11 - 12 ]. http://www. soe. ucsc. edu/- tao/pps/ Motion05. pdf
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二级参考文献18

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共引文献12

同被引文献61

  • 1陈睿,邓宇,向世明,李华.结合强度和边界信息的非参数前景/背景分割方法[J].计算机辅助设计与图形学学报,2005,17(6):1278-1284. 被引量：13
  • 2肖梅,韩崇昭.室内视频中基于边缘的运动阴影去除算法[J].模式识别与人工智能,2006,19(5):640-644. 被引量：4
  • 3郭利生,郭立,焦荣惠,郑军.一种基于运动阴影的目标检测算法[J].模式识别与人工智能,2007,20(2):180-184. 被引量：4
  • 4Yang Tao, Li S Z, Pan Quan, et al. Real-Time and Accurate Segmentation of Moving Objects in Dynamic Scene// Proc of the 2nd ACM International Workshop on Video Surveillance and Sensor Networks. New York, USA, 2004:136-143
  • 5Stauffer C, Grimson W. Learning Patterns of Activity Using Real- Time Tracking. IEEE Trans on Pattern Analysis and Machine Intelligence, 2000, 22 (8) : 747 - 757
  • 6Stenger B, Ramesh V, Paragios N, et al. Topology Free Hidden Markov Models : Application to Background Modeling//Proc of the 8th IEEE International Conference on Computer Vision. Vancouver,Canada, 2001, Ⅰ: 294-301
  • 7Martel-Brisson N, Zaccarin A. Moving Cast Shadow Detection from a Gaussian Mixture Shadow Model // Proc of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego, USA, 2005, Ⅱ: 643 -648
  • 8Porikli F, Thornton J. Shadow Flow: A Recursive Method to Learn Moving Cast Shadows//Proc of the 10th IEEE International Conference on Computer Vision. Beijing, China, 2005, Ⅰ : 891 -898
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  • 10Chen Baisheng, Lei Yunqi. Indoor and Outdoor People Detection and Shadow Suppression by Exploiting HSV Color Information // Proc of the 4th International Conference on Computer and Information Technology. Wuhan, China, 2004:137 - 142

引证文献3

二级引证文献19

模式识别与人工智能
2008年 第4期

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