Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/105557
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Title: Hierarchical rendering system based on viewpoint prediction in virtual reality
Authors: Lu, P
Zhu, F
Li, P 
Kim, J
Sheng, B
Mao, L
Issue Date: 2020
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2020, v. 12221, p. 24-32
Abstract: Virtual reality (VR) systems use multi-modal interfaces to explore three-dimensional virtual worlds. During exploration, the user may look at different objects of interest or in different directions. The field of view of human vision is 135∘× 160∘, but the one requiring the highest resolution is only in 1.5∘× 2∘. It is estimated that in modern VR, only 4% of the pixel resources of the head-mounted display are mapped to the visual center. Therefore, allocating more computing resources to the visual center and allocating fewer viewpoint prediction rendering techniques elsewhere can greatly speed up the rendering of the scene, especially for VR devices equipped with eye trackers. However, eye trackers as additional equipment may be relatively expensive and be harder to use, at the same time, there is considerable work to be done in the development of eye trackers and their integration with commercial head-mounted equipment. Therefore, this article uses an eye-head coordination model combined with the saliencey of the scene to predict the gaze position, and then uses a hybrid method of Level of Detail (LOD) and grid degeneration to reduce rendering time as much as possible without losing the perceived details and required calculations.
Keywords: Eye-head coordination
Hand track
Hierarchical rendering
LOD
VR
Publisher: Springer
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
ISBN: 978-3-030-61863-6
978-3-030-61864-3 (eBook)
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-030-61864-3_3
Description: 37th Computer Graphics International Conference, CGI 2020, Geneva, Switzerland, October 20–23, 2020
Rights: © Springer Nature Switzerland AG 2020
This version of the proceeding paper has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use(https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-030-61864-3_3.
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