Suspicious Human Activity Detection from Surveillance Videos

Video analytics is the method of processing a video, gathering data and analysing the data for getting domain specific information. In the current trend, besides analysing any video for information retrieval, analysing live surveillance videos for detecting activities that take place in its coverage area has become more important. Such systems will be implemented real time. Automated face recognition from surveillance videos becomes easier while using a training model such as Artificial Neural Network. Hand detection is assisted by skin color estimation. This research work aims to detect suspicious activities such as object exchange, entry of a new person, peeping into other’s answer sheet and person exchange from the video captured by a surveillance camera during examinations. This requires the process of face recognition, hand recognition and detecting the contact between the face and hands of the same person and that among different persons. Automation of ‘suspicious activity detection’ will help decrease error rate due to manual monitoring.