Collaborative tracking of objects in EPTZ cameras This paper addresses the issue of multisource collaborative object tracking in highdefinition (HD) video sequences. Specifically, we propose a new joint tracking paradigm for the multiple stream electronic pantiltzoom (EPTZ) cameras. These cameras are capable of transmitting a low resolution thumbnail (LRT) image of the whole field of view as well as a highresolution cropped (HRC) image for the target region. We exploit this functionality to perform joint tracking in both low resolution image of the whole field of view as well as high resolution image of the moving target. Our system detects objects of interest in the LRT image by background subtraction and tracks them using iterative coupled refinement in both LRT and HRC images. We compared the performance of our joint tracking system with that of tracking only in the HD mode. The results of our experiments show improved performance in terms of higher frame rates and better localization.

A DualCameraBased Ultrafast Tracking System for Simultaneous Multitarget Zooming In this paper, we develop a novel dualcamera system that can simultaneously capture zoomingin targets by combining an ultrafast pantilt camera and a fixed wideview camera. According to the positions of all the targets recognized with deep learning in the wideview camera, the pan and tilt angles of multiple pantilt cameras are controlled virtually on the ultrafast pantilt camera through multithread viewpoint control to simultaneously capture the zoomingin images of all the targets. Our system can generate five hundred virtual cameras with different zooming views in a second, and the effectiveness of our system is demonstrated by showing experimental results in simultaneous zoom shooting for multiple running persons and cars in the range of 70 m or more in a natural outdoor scene.