运动目标检测、阴影检测及目标跟踪中用得到的标准测试视频下载（大量IBM提供视频）

http://blog.163.com/jw_67/blog/static/136199256201039104624436/

在搜测试视频时，找到andrew31在ilovematlab论坛中分享的网址链接。我转载于此，并做出详细介绍，方便大家以后使用！

1. PETS2001的测试视频

http://www.filewatcher.com/b/ftp/ftp.cs.rdg.ac.uk/pub/PETS2001.0.0.html

内容如下，可以得到如下所示5个DATASET，有训练和测试视频：

ftp://ftp.cs.rdg.ac.uk/pub/PETS2001/ direct 532 B 2001-07-25welcome.msg 5 mirrors 6 B 2006-10-24WWW 2 mirrors 532 B 2001-07-25PETS2001_README 2 mirrors 0 2001-12-11DoNotDownLoadThisFile 2 mirrors [DIR]DATASET5/ direct 2 twin directories [DIR]DATASET4/ direct 2 twin directories [DIR]DATASET3/ direct 6 twin directories [DIR]DATASET2/ direct 6 twin directories [DIR]DATASET1/ direct 6 twin directories 0 2001-06-23.chunkdesc 2 mirrors 0 2001-06-23.bufferloc 2 mirrors

2. 阴影检测（Shadow Detection）测试视频及CVPR-ATON 阴影检测相关论文

http://cvrr.ucsd.edu/aton/shadow/

在下面原始movie可以下载到：Highway、Campus、Laboratory、Intelligent Room，这些视频。

Technical Papers A. Prati, I. Mikic, M. Trivedi, R. Cucchiara, "Detecting Moving Shadows: Formulation, Algorithms and Evaluation" (Under Review June 2001) - Survey I. Mikic, P. Cosman, G.. Kogut, M. Trivedi, "Moving Shadow and Object Detection in Traffic Scenes", International Conference on Pattern Recognition, September 2000, pp. 321-324 vol. 1 R. Cucchiara, C. Grana, M. Piccardi, A. Prati, "Detecting objects, shadows and ghosts in video streams by exploiting color and motion information", Appearing in Proceedings of 11th International Conference on Image Analysis and Processing (ICIAP 2001), September 2001. M. Trivedi, I. Mikic, G. Kogut, "Distributed Video Networks for Incident Detection and Management", IEEE Conference on Intelligent Transportation Systems, Dearborn, Michigan, October 2000. Testbed Data Comparative Movies (Highway I, Intelligent Room - AVIs) Raw Movies (Highway I, Highway II, Campus, Laboratory, Intelligent Room - AVIs) Manually Segmented Images (Ground Truth - Zipped BMPs)

3. IBM人类视觉研究中心监视系统性能评价提供的视频

http://www.research.ibm.com/peoplevision/performanceevaluation.html

这个你看了一定欣喜若狂，一大票的视频，任你选择，不用再发愁找不到视频了！

Performance Evaluation of Surveillance Systems Effectively evaluating the performance of moving object detection and tracking algorithms is in an important step towards attaining robust digital video surveillance systems with sufficient accuracy for practical applications. As systems become more complex and achieve greater robustness, the ability to quantitatively assess performance is needed in order to continuously improve performance. To this end, we are providing video sequences and ground truth annotations for performance evaluation. Ground Truth sequences have extension .pvann and are xml files. An explanation of the ground truth procedure can be found in the paper [1] . Performance metrics and an evaluation of the IBM Smart Surveillance System can also be found in this publication. 1. Outdoor Sequences ( 4 videos from PET2001 with ground truth ) PetsD1TeC1.avi PetsD1TeC1.pvann PetsD1TeC2.avi PetsD1TeC2.pvann PetsD2TeC1.avi PetsD2TeC1.pvann PetsD2TeC2.avi PetsD2TeC2.pvann 2. Indoor Sequences (11 videoswith ground truth) IndoorGTTest1.avi IndoorGTTest1.pvann IndoorGTTest2.avi IndoorGTTest2.pvann ThreePerson_Circles_Comp_0_Quad0.avi ThreePerson_Circles_Comp_0_Quad0.pvann ThreePerson_Circles_Comp_0_Quad2.avi ThreePerson_Circles_Comp_0_Quad2.pvann ThreePerson_Circles_Comp_0_Quad3.avi ThreePerson_Circles_Comp_0_Quad3.pvann ThreePerson_Together_Split_Comp_0_Quad0.avi ThreePerson_Together_Split_Comp_0_Quad0.pvann ThreePerson_Together_Split_Comp_0_Quad2.avi ThreePerson_Together_Split_Comp_0_Quad2.pvann ThreePerson_Together_Split_Comp_0_Quad3.avi ThreePerson_Together_Split_Comp_0_Quad3.pvann TwoPerson_Line_Circle_Comp_0_Quad0.avi TwoPerson_Line_Circle_Comp_0_Quad0.pvann TwoPerson_Line_Circle_Comp_0_Quad2.avi TwoPerson_Line_Circle_Comp_0_Quad2.pvann TwoPerson_Line_Circle_Comp_0_Quad3.avi TwoPerson_Line_Circle_Comp_0_Quad3.pvann [1] Performance Evaluation of Surveillance Systems Under Varying Conditions Lisa M. Brown, Andrew W. Senior, Ying-li Tian, Jonathan Connell, Arun Hampapur, Chiao-fe Shu, Hans Merkl, and Max Lu IEEE Int'l Workshop on Performance Evaluation of Tracking and Surveillance, Colorado Jan., 2005 . PDF Other Research Areas: Robust Background Subtraction Salient Motion Detection Object Classification 2D Tracking 3D Multi-Person Tracking Articulated Human Body Tracking Active Head Tracking Coarse Head Pose Estimation Position Independent Absolute Head Pose Estimation Face Cataloger Video Privacy Multi-scale Tracking & Index Browser Real Time Alerts Middleware for Large Scale Surveillance (MILS)

refer to: http://www.ilovematlab.cn/viewthread.php?tid=41981&page=1&fromuid=153920#pid382112