Feature-based tracking on a multi-omnidirectional camera dataset
Bans Evrim Demiroz, İsmail Arı, Orhan Eroglu, Albert Ali Salah, Lale Akarun · 2012
Omnidirectional cameras have a lot of potential for surveillance and ambient intelligence applications, since they provide increased coverage with fewer cameras. We introduce the new BOMNI dataset, collected with two omnidirectional cameras simultaneously. The dataset contains single subject and multi-subject interaction scenarios, as well as actions relevant for ambient assisted living, such as falling down. We describe evaluation protocols on this dataset, and provide benchmarking baseline results for two tracking systems based on bounding box and interest point matching after foreground-background segmentation, respectively.