Adaptive online camera coordination for multi-camera multi-target surveillance

Online camera selection is introduced as a result of the improved mobility of cameras and the increased scale of surveillance systems. Most existing camera assignment algorithms achieve an optimal observation under the assumption of the unlimited camera computational capacities. However, practical surveillance systems experience resource limitation and see a degradation in the system performance as the number of objects to be processed increases. To address this issue, we propose an adaptive camera assignment algorithm considering the limited camera computational capacities. In so doing, camera resources can be dynamically allocated to multiple objects according to their priorities and the current camera computational load. Experimental results illustrate that the proposed camera assignment algorithm is capable of maintaining a constant frame rate and achieving a substantially decreased object rejection rate in comparison with the algorithm presented by Bakhtari and Benhabib.

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