视频处理_跟踪和监控性能评估国际专题讨论会(PETS)2001)

IEEE International Workshop on PerformanceEvaluation of Tracking and Surveillance(PETS)2001(IEEE跟踪和监控性能评估国际专题讨论会(PETS)2001)数据摘要：PETS'2001 consists of five separate sets of training and test sequences, i.e. each set consists of one training sequence and one test sequence.All the datasets are multi-view (2 cameras) and are significantly more challenging than for PETS'2000 in terms of significant lighting variation, occlusion, scene activity and use of multi-view data.中文关键词：PETS2001,跟踪,监控,多视角,光线变化,遮挡,英文关键词：PETS2001,tracking,surveillance,multi-view,lightingvariation,occlusion,数据格式：VIDEO数据用途：Outdoor people and vehicle tracking (two synchronised views; includes omnidirectional and moving camera) (annotation available).数据详细介绍：PETS2001 DatasetsDatasetPETS'2001 consists of five separate sets of training and test sequences, i.e. each set consists of one training sequence and one test sequence.All the datasets are multi-view (2 cameras) and are significantly more challenging than for PETS'2000 in terms of significant lighting variation, occlusion, scene activity and use of multi-view data.The annotation (ground truth) for the datasets is available here.Dataset 1 (training = 3064 frames, testing = 2688 frames): Moving people and vehicles. The camera calibration may be found here.Dataset 2 (training = 2989 frames, testing = 2823 frames): Moving people and vehicles. The camera calibration may be found here.Dataset 3 (training = 5563 frames, testing = 5336 frames): Moving people. This is a more challenging sequence in terms of multiple targets and significant lighting variation. The camera calibration may be found here.Dataset 4 (training = 6789 frames, testing = 5010 frames): Moving people and vehicles (catadioptric vision) - one narrow field of view, one panoramic. The camera calibration may be found here.Dataset 5 (training = 2866 frames, testing = 2867 frames): Moving vehicle (forward and rear views). The camera calibration may be found here.For each dataset∙the training directory contains a training set of frames in both QuickTime movie format with Motion JpegA compression and as individual Jpegimages. The directory contains frame synchronised images for the two cameras.∙the test directory contains a training set of frames in both QuickTime movie format with Motion JpegA compression and as individual Jpegimages. The directory contains frame synchronised images for thetwo cameras.The annotation (ground truth) for the datasets is available here.VERY IMPORTANT INFORMATIONThe tracking results that you report in your paper submission∙should be performed using the test sequences, but the training sequences may optionally be used if the algorithms require it forlearning etc.∙may be based on a single camera view of the scene (CAMERA1), or using the dual-view data (the approach used must be clearly stated inthe paper).The tracking can be performed on the entire test sequence, or a portion of it. The images may be converted to any other format as appropriate, e.g. subsampled to half-PAL, or converted to monochrome. All results reported in the paper should clearly indicate which part of the test sequence is used, ideally with reference to frame numbers where appropriate.The tracking results must be submitted along with the paper, with the tracking results generated in XML format.This will be straightforward and should not add a significant overhead to your effort. The results you provide will be used to perform automatic performance evaluation.The paper that you submit may be based on previously published tracking methods/algorithms (including papers submitted to the main CVPR conference). The importance is that your paper MUST report results on tracking using the datasets supplied.The recommendation is that:∙you attempt to track the objects (people or vehicles or both) in Datasets1 or2 first and report tracking results on the test sequences for thesedatasets in the paper. (note that you need only use single-view databut you may use both views of the same scene (frame synchronised) if your algorithms/methods of tracking allow it.) The pre-requisite forsubmitting your paper to the workshop is that you minimally reporttracking results on either OR both of datasets 1 and 2.∙if you have been successfully completed the above, attempt Dataset 3 & possibly 4 (if you are interested in catadioptric vision) which aresignificantly longer in length and include significant lighting variation.∙Dataset 5 is primarily included for those people interested in moving cameras. Your paper may report results on this dataset alone.If you have any queries please email pets2001@.数据预览：点此下载完整数据集。