Pedestrian Detection from Thermal Images Incorporating Saliency Features

Fatih Altay, Senem Velipasalar

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

Abstract

Methods relying entirely on visible-range/color images start to have problems in detection tasks when there is not enough light to illuminate the scene. Thermal cameras, which operate based on the infrared radiation emitted by objects, can provide detectable information in low- or no-light conditions. In this paper, we propose a method to improve the performance of a pedestrian detection algorithm on thermal images by incorporating features from saliency maps to enrich the thermal image features. We employ a modified version of a state-of-the-art object detection network, and feed the thermal images and their saliency maps to two parallel networks. Experimental results on five different datasets show that our proposed approach performs better at detecting pedestrians in thermal images compared to its vanilla version and a baseline model.

Original languageEnglish (US)
Title of host publicationConference Record of the 54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1548-1552
Number of pages5
ISBN (Electronic)9780738131269
DOIs
StatePublished - Nov 1 2020
Event54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020 - Pacific Grove, United States
Duration: Nov 1 2020Nov 5 2020

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2020-November
ISSN (Print)1058-6393

Conference

Conference54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
Country/TerritoryUnited States
CityPacific Grove
Period11/1/2011/5/20

Keywords

  • Pedestrian Detection
  • Saliency Maps
  • Thermal Images

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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