Smart Surveillance System for Detecting Interpersonal Crime

We propose information processing techniques for CCTV based surveillance systems employed in (a) work environments and (b) public places and transport, for automated identification of scenes of inter-personal crime. Although both the scenarios presented in this work employ similar signal processing and learning algorithms, the objective involved are significantly different. In (a) we aim to preserve confidentiality and privacy of official meetings and discussions, while ensuring detection of unbecoming behavior, like: bullying, harassment and assault. In the proposed method we identify such critical conditions using a combination of image and speech processing and ensue conditional video recording and saving. In (b), the target is to identify the occurrence of interpersonal crime using video and voice processing, in order to raise alert at the local surveillance station, which may be receiving numerous CCTV videos from neighboring areas. This can be an assistance to the security personnel, responsible to monitor large number of screens. The proposed methods can be useful curbing interpersonal violence, and crime against women, in the form of eve teasing, and harassment.