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231226s2023 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2023.3290515
|2 doi
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|e rakwb
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|a eng
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| 100 |
1 |
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|a Zhang, Xin
|e verfasserin
|4 aut
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| 245 |
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|a Cross-Camera Trajectories Help Person Retrieval in a Camera Network
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|c 2023
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|a Text
|b txt
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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| 500 |
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|a Date Completed 13.07.2023
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|a Date Revised 18.07.2023
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a We are concerned with retrieving a query person from multiple videos captured by a non-overlapping camera network. Existing methods often rely on purely visual matching or consider temporal constraints but ignore the spatial information of the camera network. To address this issue, we propose a pedestrian retrieval framework based on cross-camera trajectory generation that integrates both temporal and spatial information. To obtain pedestrian trajectories, we propose a novel cross-camera spatio-temporal model that integrates pedestrians' walking habits and the path layout between cameras to form a joint probability distribution. Such a cross-camera spatio-temporal model can be specified using sparsely sampled pedestrian data. Based on the spatio-temporal model, cross-camera trajectories can be extracted by the conditional random field model and further optimised by restricted non-negative matrix factorization. Finally, a trajectory re-ranking technique is proposed to improve the pedestrian retrieval results. To verify the effectiveness of our method, we construct the first cross-camera pedestrian trajectory dataset, the Person Trajectory Dataset, in real surveillance scenarios. Extensive experiments verify the effectiveness and robustness of the proposed method
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|a Journal Article
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| 700 |
1 |
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|a Xie, Xiaohua
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Lai, Jianhuang
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Zheng, Wei-Shi
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 32(2023) vom: 07., Seite 3806-3820
|w (DE-627)NLM09821456X
|x 1941-0042
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| 773 |
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|g volume:32
|g year:2023
|g day:07
|g pages:3806-3820
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|u http://dx.doi.org/10.1109/TIP.2023.3290515
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|d 32
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