Effi-MAOT: A Communication-Efficient Multi-Camera Active Object Tracking

Multi-camera Active Object Tracking (AOT) has become a promising technique to continuously track the moving target in the intelligent surveillance system. The communication among cameras provides an essential way to share the information and improve the tracking performance. To achieve the efficient collaboration among cameras, we propose a novel communication-efficient multi-camera AOT system in this paper, where one camera cooperates with other cameras to realize the active object tracking by sharing its visual observations when necessary. In the proposed system, we design a binary classified neural network based switch to determine whether to communicate. Moreover, we propose an attention based communication group construction method, which allows the camera to decide who to communicate. Through the control of whether to communicate and who to communicate, many communication connections of less importance are pruned. We construct a high-fidelity environment to mimic the real-world scenario. Experimental results demonstrate that compared to the existing systems, the proposed system can significantly reduce the occupied bandwidth and achieve an improved tracking performance, especially for the high-speed moving target.