Arbitrary stereoscopic view generation using multiple omnidirectional image sequences

Maiya Hori, Masayuki Kanbara, Naokazu Yokoya

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

6 Citations (Scopus)

Abstract

This paper proposes a novel method for generating arbitrary stereoscopic view from multiple omnidirectional image sequences. Although conventional methods for arbitrary view generation with an image-based rendering approach can create binocular views, positions and directions of viewpoints for stereoscopic vision are limited to a small range. In this research, we attempt to generate arbitrary stereoscopic views from omnidirectional image sequences that are captured in various multiple paths. To generate a high-quality stereoscopic view from a number of images captured at various viewpoints, appropriate ray information needs to be selected. In this paper, appropriate ray information is selected from a number of omnidirectional images using a penalty function expressed as ray similarity. In experiments, we show the validity of this penalty function by generating stereoscopic view from multiple real image sequences.

Original languageEnglish
Title of host publicationProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
Pages286-289
Number of pages4
DOIs
Publication statusPublished - Nov 18 2010
Externally publishedYes
Event2010 20th International Conference on Pattern Recognition, ICPR 2010 - Istanbul, Turkey
Duration: Aug 23 2010Aug 26 2010

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Other

Other2010 20th International Conference on Pattern Recognition, ICPR 2010
CountryTurkey
CityIstanbul
Period8/23/108/26/10

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All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

Cite this

Hori, M., Kanbara, M., & Yokoya, N. (2010). Arbitrary stereoscopic view generation using multiple omnidirectional image sequences. In Proceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010 (pp. 286-289). [5597594] (Proceedings - International Conference on Pattern Recognition). https://doi.org/10.1109/ICPR.2010.79