The invariant features-based target tracking across multiple cameras

Target tracking across lenses is a popular research topic for video surveillance recently. This paper presents a method of target tracking across lenses with overlap regions. First, the target detection and tracking are completed with a single camera. Second, in order to obtain the location-invariant feature of the same target in the images with various cameras, the camera calibration is completed based on a three-dimension (3D) model. After that, for all images via multiple cameras, the coordinates of the 3D model are unified. Finally, referring to the assumption of spatial and temporal consistency of the target location across multiple cameras, the association among detected objects for the same target with different cameras is established. And a feature pool is built which contains perspective and scale features. Thus the same target is continuously tracked across multiple lenses. At last, the performance of the proposed approach is compared with KSP and PABC and demonstrated with indoor and outdoor experiments.