A hybrid Bayesian network learning method for constructing gene networks
Computational Biology and Chemistry
Automated Multi-Camera Surveillance: Algorithms and Practice
Automated Multi-Camera Surveillance: Algorithms and Practice
Scene Segmentation for Behaviour Correlation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
A break in the clouds: towards a cloud definition
ACM SIGCOMM Computer Communication Review
Cloud computing: future solution for e-governance
Proceedings of the 3rd international conference on Theory and practice of electronic governance
Communications of the ACM
Clustering of time series data-a survey
Pattern Recognition
Bridging the gaps between cameras
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
ACM workshop on mobile cloud media computing
Proceedings of the international conference on Multimedia
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This paper proposes a cloud-computing-based algorithmic framework which is scalable and adaptive to online smart city video sensing system. One of the most cost-expensive works in such a system is to infer the topology structure of video camera network, thus spatio-temporal relationship inference for large-scale camera network is simulated on a cloud-computing platform to validate the proposed framework. The simulation results and time complexity analysis demonstrate the effectiveness and scalability of the proposed approach.