PAVIS RGB-D

PAVIS RGB-D is a dataset for person re-identification using depth information. The main motivation is that techniques such as SDALF fail when the individuals change their clothing, therefore they cannot be used for long-term video surveillance. Depth information is the solution to deal with this problem because it stays constant for a longer period of time. The dataset is composed by four different groups of data collected using the Kinect. The first group of data has been obtained by recording 79 people with a frontal view, walking slowly, avoiding occlusions and with stretched arms ("Collaborative"). This happened in an indoor scenario, where the people were at least 2 meters away from the camera. The second ("Walking1") and third ("Walking2") groups of data are composed by frontal recordings of the same 79 people walking normally while entering the lab where they normally work. The fourth group ("Backwards") is a back view recording of the people walking away from the lab. The dataset creators provide 5 synchronized information for each person: 1) a set of 5 RGB images, 2) the foreground masks, 3) the skeletons, 4) the 3d mesh (ply), 5) the estimated floor.

Source: https://www.iit.it/research/lines/pattern-analysis-and-computer-vision/pavis-datasets/534-rgb-d-person-re-identification-dataset Image Source: https://www.iit.it/research/lines/pattern-analysis-and-computer-vision/pavis-datasets/534-rgb-d-person-re-identification-dataset