Accuracy Improvement of Human Tracking in Aerial Images Using Error Correction Based on Color Information

Risako Aoki, Takuro Oki, Ryusuke Miyamoto

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

Abstract

The authors are trying to construct a real-time vital sensing system during exercise where humans wearing sensor nodes move quickly and their density becomes sometimes higher. In this case, existing multi-hop networking using RSSI or GPS to gather vital signs exercisers may not work appropriately. To solve this problem, the authors are proposing image-assisted routing (shortly IAR) that estimates the locations of sensor nodes by image processing. This paper proposes a tracking scheme with error correction based on color information, which is indispensable for IAR. Experimental results using actual images taken from a UAV showed that the proposed scheme achieved accurate tracking using only simple operations without sophisticated state estimation and computationally exhaustive deep learning: MT reached 100% by the proposed scheme.

Original languageEnglish
Title of host publicationProceedings of the 2020 9th International Conference on Software and Computer Applications, ICSCA 2020
PublisherAssociation for Computing Machinery
Pages124-128
Number of pages5
ISBN (Electronic)9781450376655
DOIs
Publication statusPublished - 18 Feb 2020
Event9th International Conference on Software and Computer Applications, ICSCA 2020 - Langkawi, Malaysia
Duration: 18 Feb 202021 Feb 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference9th International Conference on Software and Computer Applications, ICSCA 2020
CountryMalaysia
CityLangkawi
Period18/02/2021/02/20

Keywords

  • color Information
  • Error Correction
  • Simple Computation
  • Visual Object Tracking

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