Museumvisitors: a dataset for pedestrian and group detection, gaze estimation and behavior understanding

In this paper we describe a new dataset, under construc-tion, acquired inside the National Museum of Bargello in Florence. It was recorded with three IP cameras at a res-olution of 1280 × 800 pixels and an average framerate of five frames per second. Sequences were recorded following two scenarios. The first scenario consists of visitors watch-ing different artworks (individuals), while the second one consists of groups of visitors watching the same artworks (groups). This dataset is specifically designed to support re-search on group detection, occlusion handling, tracking, re-identification and behavior analysis. In order to ease the annotation process we designed a user friendly web in-terface that allows to annotate: bounding boxes, occlusion area, body orientation and head gaze, group belonging, and artwork under observation. We provide a comparison with other existing datasets that have group and occlusion anno-tations. In order to assess the difficulties of this dataset we have also performed some tests exploiting seven represen-tative state-of-the-art pedestrian detectors. 1