CrowdTracker: Object tracking using mobile crowd sensing

Yao Jing, Bin Guo, Yan Liu, Zhu Wang, Zhiwen Yu, Xingshe Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

This paper proposes CrowdTracker, a novel object tracking system based on mobile crowd sensing (MCS). Different from traditional video-based studies, CrowdTracker recruits people to collaboratively take photos of the object to achieve object movement prediction and tracking. The optimization objective of CrowdTracker is to effectively track the moving object in real time and minimize the cost on user incentives. Specifically, the incentive is determined by the number of workers assigned and the total distance that workers move to complete the task. In order to achieve the objective, we propose the MPRE model to predict the object movement and two other algorithms, namely Tcentric and P-centric, for task allocation. Initial experimental results over a large-scale real-world dataset indicate that CrowdTracker can effectively track the object with a low incentive cost.

Original languageEnglish
Title of host publicationUbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
PublisherAssociation for Computing Machinery, Inc
Pages85-88
Number of pages4
ISBN (Electronic)9781450351904
DOIs
StatePublished - 11 Sep 2017
Event2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017 - Maui, United States
Duration: 11 Sep 201715 Sep 2017

Publication series

NameUbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers

Conference

Conference2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017
Country/TerritoryUnited States
CityMaui
Period11/09/1715/09/17

Keywords

  • Mobile crowd sensing
  • Object movement prediction
  • Object tracking
  • Photo taking
  • Task allocation

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