Multi-camera Based Human Tracking with Non-overlapping Fields of View

This paper presents approach for an automated surveillance system which performs human detection and tracking across multiple non-overlapping cameras. Emphasis is put at single camera level where motion based segmentation is achieved using optical flow estimation. Feature matching and region-based shape descriptors are used for tracking. The proposed approach then extends feature and region-based shape matching across fields of view (FOV) of multiple non-overlapping cameras in order to obtain inter-camera correspondences. Evaluation of the system was performed in different scenarios which verify that the proposed method can efficiently perform video motion tracking with high processing speeds.