The growing interest on People Re-identification for surveillance forensics multimedia search action analysis calls for public and challenging datasets to train and test proposed solutions. Re-identification can exploit appearance features extracted by images but also motion and spatio-temporal features when videos and possibly camera calibration are available. Currently available datasets are not sufficient to cover all the aspects and the requirements of state of the art techniques.3D-PES would like to give annotation data for people segmentation, people tracking, people 3D reconstruction under calibrated scenarios, people search and re-identification by providing more videos with the same individuals captured from different points of view in real urban scenario.The new benchmark extends the previously published Visor-SARC3D dataset and now contains:More than 600 videos of 200 people from 8 static camerasSegmented key-frames for each personReference background imagesCamera calibration dataStructured annotation on DB: key frames people detections3D scene reconstructionRelated publication:D. Baltieri R. Vezzani R. Cucchiara, "3DPes: 3D People Dataset for Surveillance and Forensics", in Proceedings of the 1st International ACM Workshop on Multimedia access to 3D Human Objects Scottsdale Arizona USA Nov 28 - Dec 1 2011This dataset is part of theViSorproject