We propose EGO-CH, a dataset of egocentric videos for visitors’ behavior understanding. The dataset has been collected in two different cultural sites and includes more than 27 hours of video acquired by 70 subjects, including volunteers and 60 real visitors. The overall dataset includes labels for 26 environments and over 200 Points of Interest (POIs). Specifically, each video of EGO-CH has been annotated with 1) temporal labels specifying the current location of the visitor and the observed POI, 2) bounding box annotations around POIs. A large subset of the dataset, consisting of 60 videos,is also associated with surveys filled out by the visitors at the end of each visit. To encourage researchon the topic, we propose 4 challenging tasks useful to understand visitors’ behavior and report baseline results on the dataset
The dataset has been acquired using a head-mounted Microsoft HoloLens device in two cultural sites located in Sicily,Italy: 1) “Palazzo Bellomo”, located in Siracusa, and 2) “Monastero dei Benedettini”, located in Catania.
EGO-CH: Palazzo Bellomo
F. Ragusa, A. Furnari, S. Battiato, G. Signorello, G. M. Farinella. EGO-CH: Dataset and Fundamental Tasks for Visitors Behavioral Understanding using Egocentric Vision. Pattern Recognition Letters - Special Issue on Pattern Recognition and Artificial Intelligence Techniques for Cultural Heritage, 2020. Download the paper.