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
Country/TerritoryJapan
CitySapporo City, Hokkaido
Period14-04-2614-04-28

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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