The TrackVes dataset provides to the computer assisted surgery community a dataset for the validation of soft tissue tracking algorithms. It is composed of nine folders: EV1:3 - 3 video sequences of ex-vivo organs (kidney and liver); IV1:6 - 6 video sequences of in-vivo organs (real abdominal surgical scenes); Each folder contains: videoLeft.avi - video sequence; GT.xml - xml file with ground truth defined as a 2D polygon around the area to be tracked, with an interframe step of 10; Attributes.xml - xml file indicating one of the following attributes associated to each frame (with an interframe step of 10): 0 - Safety Area Visible (SAV); 1 - Partial Occlusion (PO); 2 - Safety Area Out of Field of View (OFV); 3 - Total Occlusion (TO); 4 - DEFormation (DEF); 5 - Illumination Changes (IC); 6 - Abrupt Camera Motion (ACM); 7 - Blur (BLR); 8 - Presence of Smoke (SMK). The C++ code implementing the ground truth generation and the tracking algorithm evaluation is available on Bitbucket - https://bitbucket.org/ververo/envisors_track/ as: app/gt_generator app/tracking_evaluation. If you use this dataset, please cite: V. Penza, X. Du, D. Stoyanov, A. Forgione, L. Mattos and E. De Momi. "Long Term Safety Area Tracking (LT-SAT) with Online Failure Detection and Recovery for Robotic Minimally Invasive Surgery", Medical Image Analysis, 2017. For further information, please contact veronica.penza@iit.it

{"references": ["V. Penza, X. Du, D. Stoyanov, A. Forgione, L. Mattos and E. De Momi. \"Long Term Safety Area Tracking (LT-SAT) with Online Failure Detection and Recovery for Robotic Minimally Invasive Surgery\", Medical Image Analysis, 2017."]}