Published October 25, 2017 | Version v1
Journal article Open

Optimizing the Detection Performance of Smart Camera Networks Through a Probabilistic Image-Based Model


Networks of smart cameras, equipped with on-board processing and communication infrastructure, are increasingly being deployed in a variety of different application fields, such as security and surveillance, traffic monitoring, industrial monitoring, and critical infrastructure protection. The task(s) that a network of smart cameras executes in these applications, e.g., activity monitoring, object identification, can be severely degraded because of errors in the detection module. However, in most cases higher-level tasks and decision making processes in smart camera networks (SCNs) assume ideal detection capabilities for the cameras, which is often not the case due to the probabilistic nature of the detection process, especially for low-cost cameras with limited capabilities. Realizing that it is necessary to introduce robustness in the decision process this paper presents results towards uncertainty-aware SCNs. Specifically, we introduce a flexible uncertainty model that can be used to characterize the detection behaviour in a camera network. We also show how to utilize the model to formulate detectionaware optimization algorithms that can be used to reconfigure the network in order to improve the overall detection efficiency and thus increase the effective number of detected targets. We evaluate our proposed model and algorithms using a network of Raspberry-Pi-based smart cameras that reconfigure in order to improve the detection performance based on the position of targets in the area. Experimental results in the lab as well as in a human monitoring application and extensive simulation results, indicate that the proposed solutions are able to improve the robustness and reliability of SCNs.


© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works." C. Kyrkou, E. Christoforou, S. Timotheou, T. Theocharides, C. Panayiotou and M. Polycarpou, "Optimizing the Detection Performance of Smart Camera Networks Through a Probabilistic Image-Based Model," in IEEE Transactions on Circuits and Systems for Video Technology, vol. PP, no. 99, pp. 1-1. doi: 10.1109/TCSVT.2017.2651362 keywords: {Decision making;Monitoring;Optimization;Probabilistic logic;Smart cameras;Uncertainty;Active Vision;Dynamic Reconfiguration,;Embedded Vision Systems;Optimization Methods;Smart Camera Networks}, URL:


Optimizing the Detection Performance of Smart Camera Networks Through a Probabilistic Image-Based Model.pdf

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KIOS CoE – KIOS Research and Innovation Centre of Excellence 739551
European Commission
FAULT-ADAPTIVE – Fault-Adaptive Monitoring and Control of Complex Distributed Dynamical Systems 291508
European Commission