计算机科学 ›› 2014, Vol. 41 ›› Issue (3): 293-296.
向金海,廖红虹,樊恒,代江华,孙伟平,余胜生
XIANG Jin-hai,LIAO Hong-hong,FAN Heng,DAI Jiang-hua,SUN Wei-ping and YU Sheng-sheng
摘要: 对运动的真实前景目标进行实时提取是监控视频中的一个基本步骤。在前景提取过程中,阴影消除一直是一个较难解决的问题。为解决此问题,根据光照模型提出了局部强度比率模型,并证明其具有光照不变性特征。同时证明,如果视频图像噪声高斯分布,则局部强度比率也满足高斯分布。在通过高斯混合模型获取前景的过程中,用局部强度比率代替像素值进行处理,得到消除阴影后的前景。实验表明,本方法在不同的场景下可以有效地消除阴影,得到无阴影的前景,同其他方法比较,显示出较好的性能。
[1] Piccardi M.Background subtraction techniques:a review [C]∥IEEE International Conference on Systems,Man and Cyberne-tics.2004:3099-3104 [2] Sanin A,Sanderson C,Lovell B.Shadow detection:A survey and comparative evaluation of recent methods[J].Pattern Recognition,2012,45:1684-1695 [3] Al-Najdawi N,Bez H E,Singhai J,et al.A survey of cast shadow detection algorithms[J].Pattern Recognition Letters,2012,3:752-764 [4] Joshi A,Papanikolopoulos N.Learning to detect moving sha-dows in dynamic environments[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2008,30(11):2055-2063 [5] Liu Z,Huang K,Tan T,et al.Cast shadow removal combining local and global features[C]∥IEEE Conference on Computer Vision and Pattern Recognition.2007:1-8 [6] Martel-Brisson N,Zaccarin A.Learning and removing cast sha-dows through a multi distribution approach[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2007,29(7):1133-1146 [7] Porikli F,Thornton J.Shadow flow:a recursive method to learn moving cast shadows[C]∥Tenth IEEE International Conference on Computer Vision.2005:891-898 [8] 查宇飞,楚瀛,王勋,等.一种基于Boosting判别模型的运动阴影检测方法[J].计算机学报,2007,0(8):1295-2113 [9] 韩忠民,刘志,张兆杨,等.视频分割中运动阴影消除的新方法[J].中国图象图形学报,2009,4(10):2110-2113 [10] Nadimi S,Bhanu B.Physical models for moving shadow and object detection in video[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2004,26(8):1079-1087 [11] Huang J-B,Chen C-S.Moving cast shadow detection using phy-sics-based features[C]∥IEEE Conference on Computer Vision and Pattern Recognition.2009:2310-2317 [12] Martel-Brisson N,Zaccarin A.Kernel-based learning of castshadows from a physical model of light sources and surfaces for low-level segmentation[C]∥IEEE Conference on Computer Vision and Pattern Recognition.2008:1-8 [13] Chen C-C,Aggarwal J.Human shadow removal with unknown light source[C]∥International Conference on Pattern Recognition.2010:2407-2410 (下转封三)(上接第296页) [14] Hsieh J-W,Hu W-F,Chang C-J,et al.Shadow elimination foreffective moving object detection by Gaussian shadow modeling[J].Image and Vision Computing,2003,21(6):505-516 [15] Nicolas H,Joint J-M P.moving cast shadows segmentation and light source detection in video sequences[J].Signal Processing:Image Communication,2006,21(1):22-43 [16] Zhang W,Fang X Z,Yang X K,et al.Moving cast shadows detection using ratio edge[J].IEEE Trans.Multimedia,2007,9:1202-1213 [17] Stander J,Mech R,Ostermann J.Detection of moving cast sha-dows for object segmentation[J].IEEE Trans.Multimedia,1999,1:65-76 [18] Andersen M S,Jensen T,Madsen C B.Estimation of DynamicLight Changes in Outdoor Scenes Without the use of Calibration Objects[C]∥18th Int.Conf.Pattern Recognition.2006,4:91-94 [19] Stauffer C,Grimson W E L.Adaptive background mixture models for real-time tracking[C]∥IEEE Computer Society Conf.Computer Vision and Pattern Recognition.1999,2:637-663 [20] Prati A,Mikic I,Trivedi M M,et al.Detecting Moving Sha-dows:Algorithms and Evaluation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2003,25(7):918-923 |
No related articles found! |
|