Detecting Foot-Chases from Police Body-Worn Video

Existing methods to record interactions between the public and police officers are unable to capture the entirety of police-public interactions. In order to provide a comprehensive understanding of these interactions, the Los Angeles Police Department (LAPD) intends to utilize Body-Worn Video (BWV) collected from cameras fastened to their officers. BWV provides a novel means to collect fine-grained information about police-public interactions. The purpose of this project is to identify foot-chases from the videos using machine-learning algorithms. Our proposed algorithm uses the Bag-of-Intrinsic-Words algorithm followed by classification via support-vector machines. Our training dataset consists of 100 training videos (20 foot-chase & 80 non-foot-chase), and a test dataset of 60 LAPD videos (4 foot-chase & 56 non-foot-chase). We achieved results of 91.6% testing accuracy.