A novel fuzzy based home occupant monitoring system using kinect cameras
IEEE Computer Society
School of Computer and Security Science
In this paper, an approach is presented for the detection of abnormal behaviours in the activities of people living alone in their homes. The proposed approach takes input from Kinect cameras and extracts a number of visual attributes that represent the occupant's location and orientation. A set of fuzzy logic parameters is first learnt from the training data. Next the proposed approach learns epochs of activities in each location and then generates models of normal behaviour patterns. Unusual behaviour is then detected in subsequent data by looking for patterns which differ from the learnt normal behaviours based on their time of occurrence, visual attributes, or duration. Experiments conducted showed the effectiveness of the proposed system. © 2015 IEEE.
Not open access