Detection of Object Throwing Behavior in Surveillance Videos

arXiv:2403.06552v1 Announce Type: new
Abstract: Anomalous behavior detection is a challenging research area within computer vision. Progress in this area enables automated detection of dangerous behavior using surveillance camera feeds. A dangerous behavior that is often overlooked in other research is the throwing action in traffic flow, which is one of the unique requirements of our Smart City project to enhance public safety. This paper proposes a solution for throwing action detection in surveillance videos using deep learning. At present, …

abstract arxiv automated behavior behavior detection computer computer vision cs.cv detection flow object progress research surveillance traffic type videos vision