[1] Zivkovic Z,van der Heijden F.Recursive unsupervised learning of finite mixture models[J].IEEE Trans.on PAMI,2004,26(5):651-656

[2] Stauffer C,Grimson W.Adaptive background mixture models for real-time tracking[J].Proc.of IEEE Int.Conf.on CVPR,1999,2:246-252

[3] Dar-shyang Lee.Effective Gaussian mixture learning for video background subtraction[J].IEEE Trans.on PAMI,2005,27(5):827-832

[4] Cheng J.Flexible background mixture models for foreground segmentation[J].Image and Vision Computing,2006,24:473-482

[5] Bai Sheng C,Yun Qi L.Indoor and outdoor people detection and shadow suppression by exploiting HSV color information[C]//Proceedings of the Fourth International Conference on Computer and Information Technology.Wuhan,China:IEEE Computer Society,2004:137-142

[6] McKenna S J.Tracking groups of people[J].CVIU,2000,80:42-56

[7] Prati A,Mikic I.Detecting moving shadows:algorithms and evaluation[J].IEEE Trans.on PAMI,2003,25(7):918-923

[8] Cucchiara R.Improving shadow suppression in moving object detection with HSV color information[J].Proc of lntel.Transportation Systems Conf,2001:334-339

[9] XU L Q,J L Landabaso.Segmentation and tracking of multiple moving objects for intelligent video analysis[J].BT Technology Journal,2004,22(3):140-149