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Target Handoff with Appearance Model Inheriting and Learning
Wenhui Dong,Peishu Qu 보안공학연구지원센터 2014 International Journal of Signal Processing, Image Vol.7 No.5
We address the issue of continuous tracking of the target in an environment covered by multiple cameras. In such a scenario, target handoff is a key problem. In this paper, we propose a novel target handoff method based on appearance model inheriting and learning. The appearance model is initially learned by sparse representation using the tracking results in the first camera. The next camera inherits the appearance model for target handoff and updates it after getting the whole tracking results. Then, the appearance model is transferred to the following camera. By the appearance model inheriting and learning, the appearance model can describe the target more and more precisely, which will make the target handoff more accurately and effectively. We also demonstrate the performance of our method on several video surveillance sequences.
Topology Learning of Non-overlapping Multi-camera Network
Xiaolin Li,Wenhui Dong,Faliang Chang,Peishu Qu 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.11
We focus on the issue of learning the topology of the non-overlapping multi-camera network, which includes recovering the nodes (entry and exit zones), transition time distribution and links. Firstly, the nodes associated with each camera view are identified using clustering method. Then, transition time distribution is modeled as a Gaussian distribution and is computed by accumulated cross correlation and Gaussian fitting. Finally, the mutual information is used to refine the possible links and the topology is recovered. Experimental results on simulated data and real scene demonstrate the effectiveness of the proposed method.