Matteo Taiana
PhD student in Computer Vision and Robotics.
Data sets
Improved annotation for the INRIA person data set. The INRIA person data set is very popular in the Pedestrian Detection community, both for training detectors and reporting results. Yet, its labelling has some limitations: some of the pedestrians are not labelled, there is no specific label for the ambiguous cases and the information on the visibility ratio of each person is missing. We collected a new labelling that overcomes such limitations and can be used to evaluate the performance of detection algorithms in a more truthful way. It also allows researchers to test the influence of partial occlusion and pedestrian height during training training on the detection performance. The labels are encoded in the format used for the Caltech Pedestrian Detection Benchmark, in two vbb files. New Training labels - Download New Test labels - Download
HDA Dataset: High Definition Analytics Camera Network at ISR. HDA is a multi-camera high-resolution image sequence dataset for research on high-definition surveillance. 18 cameras (including VGA, HD and Full HD resolution) were recorded simultaneously during 30 minutes in a typical indoor office scenario at a busy hour (lunch time) involving more than 80 persons. Each frame is labeled with Bounding Boxes tightly adjusted to the visible body of the persons, the unique identification of each person, and flag bits indicating occlusion and crowd. HDA Dataset page