Human detection based on a sequence of thermal images using deep learning

X. Wang*, S. Hosseinyalamdary

*Corresponding author for this work

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

10 Citations (Scopus)
45 Downloads (Pure)

Abstract

Human detection has been playing an increasingly important role in many fields in recent years. Human detection is a still challenging task because, for the group of people, each individual has his unique appearance and, body shape. Compared with the traditional method, the deep learning neural network has the advantages of shorter computing time, higher accuracy and easier operation. Therefore, deep learning method has been widely used in object detection. The current state of art in human detection is RetinaNet. Among all the deep learning approaches, RetinaNet gives the highest accuracy of human detection (Lin, Goyal, Girshick, He, & Piotr Dollar, 2018).The temporal component of video provides additional and significant clues as compared to the static image. In this paper, the temporal relationship of the images is utilized to improve the accuracy of human detection. Compared to using only an image, the accuracy of human detection is 21.4% higher when a sequence of images is applied. .

Original languageEnglish
Title of host publicationThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
EditorsG. Vosselman, S.J. Oude Elberink, M.Y. Yang
PublisherInternational Society for Photogrammetry and Remote Sensing (ISPRS)
Pages127-132
Number of pages6
Volume42
Edition2/W13
DOIs
Publication statusPublished - 4 Jun 2019
Event4th ISPRS Geospatial Week 2019 - University of Twente, Enschede, Netherlands
Duration: 10 Jun 201914 Jun 2019
Conference number: 4
https://www.gsw2019.org/

Publication series

NameInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
PublisherCopernicus
ISSN (Print)1682-1750

Conference

Conference4th ISPRS Geospatial Week 2019
Country/TerritoryNetherlands
CityEnschede
Period10/06/1914/06/19
Internet address

Keywords

  • Deep learning
  • Human detection
  • Temporal consistency
  • Thermal images
  • ITC-GOLD

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