OmniView: An Exploratory Study of 360 Degree Vision using Dynamic Distortion based on Direction of Interest

Feng Liang, Stevanus Kevin, Holger Baldauf, Kai Kunze, Yun Suen Pai

研究成果: Conference contribution

抄録

The possibility of providing humans with a 360 field of view (FOV) is an area that has fascinated researchers for some time. We introduce OmniView, an exploratory study to determine an optimized 360 FOV vision using dynamic distortion methods for reducing distortion and enlarging the area of the direction of interest. We developed three variations of OmniView to trigger distortions: eye gaze selection, pointing selection, and automatic selection. Our first study (n=16) compares these methods with no dynamic distortion (equirectangular view) in terms of spatial perception change and reaction time. The second study (n=16) evaluated subjective simulator sickness while performing simple everyday tasks. There is no significant change between OmniView and a no distortion baseline regarding spatial perception and reaction time. However, there is a statistically significant rise in disorientation from before the study to after using Pointing OmniView and Automatic OmniView. Most users (n=13) have a strong preference towards Gaze OmniView. From the results, we provide design guidelines towards further optimizing 360 vision and preserving our spatial sense and reaction time while keeping simulator sickness to a minimum.

本文言語English
ホスト出版物のタイトルProceedings of the Augmented Humans International Conference, AHs 2020
出版社Association for Computing Machinery
ISBN(電子版)9781450376037
DOI
出版ステータスPublished - 2020 3 16
イベント2020 Augmented Humans International Conference, AHs 2020 - Kaiserslautern, Germany
継続期間: 2020 3 162020 3 17

出版物シリーズ

名前ACM International Conference Proceeding Series

Conference

Conference2020 Augmented Humans International Conference, AHs 2020
CountryGermany
CityKaiserslautern
Period20/3/1620/3/17

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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