Understanding head-mounted display FOV in maritime search and rescue object detection

Susannah Soon, Artur Lugmayr, Andrew Woods, Tele Tan

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

3 Citations (Scopus)

Abstract

Object detection when viewing Head Mounted Display (HMD) imagery for maritime Search and Rescue (SAR) detection tasks poses many challenges, for example, objects are difficult to distinguish due to low contrast or low observability. We survey existing Artificial Intelligence (AI) image processing algorithms that improve object detection performance. We also examine central and peripheral vision (HVS) and their relation to Field of View (FOV) within the Human Visual System when viewing such images using HMDs. We present results from our user-study which simulates different maritime scenes used in object detection tasks. Users are tested viewing sample images with different visual features over different FOVs, to inform the development of an AI algorithm for object detection.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2018
PublisherIEEE
Pages116-119
Number of pages4
ISBN (Electronic)9781538692691
DOIs
Publication statusPublished - 15 Jan 2019
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Artificial Intelligence and Virtual Reality - Taichung, Taiwan, Republic of China
Duration: 10 Dec 201812 Dec 2018
Conference number: 1

Conference

ConferenceIEEE International Conference on Artificial Intelligence and Virtual Reality
Abbreviated titleAIVR
CountryTaiwan, Republic of China
CityTaichung
Period10/12/201812/12/2018

Keywords

  • AI
  • Central vision
  • Field of view
  • FOV
  • Head Mounted Display
  • Human visual system
  • Human-Computer-Interaction
  • Maritime search and rescue
  • Peripheral vision

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