Welcome to the CVPR 2017 Detection and Tracking in low-density scenarios Challenge!

This challenge follows the benchmarking of detection and tracking algorithms as set in PETS 2016.  The task is to detect and/or track objects in all frames from video sequences corresponding to this category and report detected/tracked objects at each frame in the MOT Challenge. Authors will be addressing the video sequences contained in the PETS datasets where the density of targets to track is low.  While this task has been addressed traditionally by the community, it still remains an open problem. Not only well known challenges on illumination and occlusion still perturb tracking algorithms but also tracking on different application domains bring specific challenges. Tracking algorithms in the maritime domain, for instance, have to deal with water wakes and waves to accurately detect and track an object, even as a single target. PETS datasets will allow authors to evaluate detection and tracking algorithms on two domains: (1) pedestrian and (2) maritime applications where the density of targets to track is low but the conditions are challenging.