Networking Humans, Robots and Environments

This book dives into the heart of how to design distributed control architectures for heterogeneous teams of humans, robots, and automated systems, enabling them to achieve greater cooperation and ...
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Collaborative Crowd Surveillance Using Networked Robotic Cameras

Pp. 18-42 (25)

Yiliang Xu and Dezhen Song

Abstract

We report an autonomous surveillance system with multiple networked pantilt- zoom (PTZ) cameras assisted by a fixed wide-angle camera. The wide-angle camera provides large but low resolution coverage and detects and tracks all moving objects in the scene. Based on the output of the wide-angle camera, the system generates spatiotemporal observation requests for each moving object, which are candidates for close-up views using PTZ cameras. Due to the fact that there are usually much more objects than the number of PTZ cameras, the system first assigns a subset of the requests/objects to each PTZ camera. The PTZ cameras then select the parameter settings that best satisfy the assigned competing requests to provide high resolution views of the moving objects. We propose an approximation algorithm to solve the request assignment and the camera parameter selection problems in real time. The effectiveness of the proposed system is validated in comparison with an existing work using simulation. The simulation results show that in heavy traffic scenarios, our algorithm increases the number of observed objects by over 210%.

Affiliation:

Department of Computer Science and Engineering Texas A&M University College Station, TX 77843, USA