Unsupervised path modeling across multiple cameras with disjoint views for foreground object tracking

Di Kai Yang, Pau-Choo Chung, Chun Rong Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We present an unsupervised path modeling method to track foreground objects across multiple cameras with disjoint views. To avoid the training process in most approaches, our method imposes the camera topology graph to identify possible paths of foreground objects in the camera network. Then, with the appearance and temporal information, dynamic programming is applied to search an optimal path of a target foreground object with a given length of the path. The experimental results show that the proposed method can successfully track target objects across multiple cameras with disjoint views compared to the state-of-the-Art supervised methods.

Original languageEnglish
Title of host publicationProceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014
EditorsXiaohong Jiang, Shaozi Li, Yun Cheng, Ying Dai
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1161-1165
Number of pages5
ISBN (Electronic)9781479931965
DOIs
Publication statusPublished - 2014 Nov 5
Event2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014 - Sapporo City, Hokkaido, Japan
Duration: 2014 Apr 262014 Apr 28

Publication series

NameProceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014
Volume2

Other

Other2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014
CountryJapan
CitySapporo City, Hokkaido
Period14-04-2614-04-28

Fingerprint

Cameras
Dynamic programming
Topology

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Yang, D. K., Chung, P-C., & Huang, C. R. (2014). Unsupervised path modeling across multiple cameras with disjoint views for foreground object tracking. In X. Jiang, S. Li, Y. Cheng, & Y. Dai (Eds.), Proceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014 (pp. 1161-1165). [6947853] (Proceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014; Vol. 2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/InfoSEEE.2014.6947853
Yang, Di Kai ; Chung, Pau-Choo ; Huang, Chun Rong. / Unsupervised path modeling across multiple cameras with disjoint views for foreground object tracking. Proceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014. editor / Xiaohong Jiang ; Shaozi Li ; Yun Cheng ; Ying Dai. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 1161-1165 (Proceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014).
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abstract = "We present an unsupervised path modeling method to track foreground objects across multiple cameras with disjoint views. To avoid the training process in most approaches, our method imposes the camera topology graph to identify possible paths of foreground objects in the camera network. Then, with the appearance and temporal information, dynamic programming is applied to search an optimal path of a target foreground object with a given length of the path. The experimental results show that the proposed method can successfully track target objects across multiple cameras with disjoint views compared to the state-of-the-Art supervised methods.",
author = "Yang, {Di Kai} and Pau-Choo Chung and Huang, {Chun Rong}",
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Yang, DK, Chung, P-C & Huang, CR 2014, Unsupervised path modeling across multiple cameras with disjoint views for foreground object tracking. in X Jiang, S Li, Y Cheng & Y Dai (eds), Proceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014., 6947853, Proceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014, vol. 2, Institute of Electrical and Electronics Engineers Inc., pp. 1161-1165, 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014, Sapporo City, Hokkaido, Japan, 14-04-26. https://doi.org/10.1109/InfoSEEE.2014.6947853

Unsupervised path modeling across multiple cameras with disjoint views for foreground object tracking. / Yang, Di Kai; Chung, Pau-Choo; Huang, Chun Rong.

Proceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014. ed. / Xiaohong Jiang; Shaozi Li; Yun Cheng; Ying Dai. Institute of Electrical and Electronics Engineers Inc., 2014. p. 1161-1165 6947853 (Proceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014; Vol. 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - We present an unsupervised path modeling method to track foreground objects across multiple cameras with disjoint views. To avoid the training process in most approaches, our method imposes the camera topology graph to identify possible paths of foreground objects in the camera network. Then, with the appearance and temporal information, dynamic programming is applied to search an optimal path of a target foreground object with a given length of the path. The experimental results show that the proposed method can successfully track target objects across multiple cameras with disjoint views compared to the state-of-the-Art supervised methods.

AB - We present an unsupervised path modeling method to track foreground objects across multiple cameras with disjoint views. To avoid the training process in most approaches, our method imposes the camera topology graph to identify possible paths of foreground objects in the camera network. Then, with the appearance and temporal information, dynamic programming is applied to search an optimal path of a target foreground object with a given length of the path. The experimental results show that the proposed method can successfully track target objects across multiple cameras with disjoint views compared to the state-of-the-Art supervised methods.

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M3 - Conference contribution

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Yang DK, Chung P-C, Huang CR. Unsupervised path modeling across multiple cameras with disjoint views for foreground object tracking. In Jiang X, Li S, Cheng Y, Dai Y, editors, Proceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 1161-1165. 6947853. (Proceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014). https://doi.org/10.1109/InfoSEEE.2014.6947853