Occluded-PoseTrack-ReID (Occluded-PoseTrack Re-Identification)

We introduce Occluded PoseTrack-ReID (or simply Occ-PTrack), a new ReID dataset we built out of the annotation available with PoseTrack21, a popular video benchmark for multi-person pose tracking, that features keypoints and cross-video identity annotations. Unlike previous ReID datasets focused on street surveillance, Occ-PTrack consists of images from everyday life videos, primarily from sports activities. Occ-PTrack is divided into a train/test that includes 1000/1411 identities with 17.898/13.412 images from 474/170 videos, which is roughly equivalent in terms of scale to other popular ReID datasets (e.g. Market-1501, Occluded-Duke, ...). To assess the ReID model’s performance in multi-person occlusion scenarios, we select the most cluttered images of each identity in the test set as query samples, and the remaining test images as gallery samples. Cluttered images corresponds to multi-persons occlusions scenarios where either the front (occluding) or back (occluded) person is the ReID target, to evaluate the model ability to re-identify individuals in both scenarios. We provide further details about our proposed dataset in the supp. materials. Occ-PTrack is challenging as persons within the same video exhibit a high degree of visual resemblance since they often wear similar sports kits.