Novel stereoscopic view generation by image-based rendering coordinated with depth information

Maiya Hori, Masayuki Kanbara, Naokazu Yokoya

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

11 Citations (Scopus)

Abstract

This paper describes a method of stereoscopic view generation by image-based rendering in wide outdoor environments. The stereoscopic view can be generated from an omnidirectional image sequence by a light field rendering approach which generates a novel view image from a set of images. The conventional methods of novel view generation have a problem such that the generated image is distorted because the image is composed of parts of several omnidirectional images captured at different points. To overcome this problem, we have to consider the distances between the novel viewpoint and observed real objects in the rendering process. In the proposed method, in order to reduce the image distortion, stereoscopic images are generated considering depth values estimated by dynamic programming (DP) matching using the images that are observed from different points and contain the same ray information in the real world. In experiments, stereoscopic images in wide outdoor environments are generated and displayed.

Original languageEnglish
Title of host publicationImage Analysis - 15th Scandinavian Conference, SCIA 2007, Proceedings
Pages193-202
Number of pages10
Publication statusPublished - Dec 1 2007
Externally publishedYes
Event15th Scandinavian Conference on Image Analysis, SCIA 2007 - Aalborg, Denmark
Duration: Jun 10 2007Jun 14 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4522 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th Scandinavian Conference on Image Analysis, SCIA 2007
CountryDenmark
CityAalborg
Period6/10/076/14/07

Fingerprint

Image-based Rendering
Dynamic programming
Experiments
Rendering
Image Sequence
Dynamic Programming
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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Hori, M., Kanbara, M., & Yokoya, N. (2007). Novel stereoscopic view generation by image-based rendering coordinated with depth information. In Image Analysis - 15th Scandinavian Conference, SCIA 2007, Proceedings (pp. 193-202). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4522 LNCS).

Novel stereoscopic view generation by image-based rendering coordinated with depth information. / Hori, Maiya; Kanbara, Masayuki; Yokoya, Naokazu.

Image Analysis - 15th Scandinavian Conference, SCIA 2007, Proceedings. 2007. p. 193-202 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4522 LNCS).

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

Hori, M, Kanbara, M & Yokoya, N 2007, Novel stereoscopic view generation by image-based rendering coordinated with depth information. in Image Analysis - 15th Scandinavian Conference, SCIA 2007, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4522 LNCS, pp. 193-202, 15th Scandinavian Conference on Image Analysis, SCIA 2007, Aalborg, Denmark, 6/10/07.
Hori M, Kanbara M, Yokoya N. Novel stereoscopic view generation by image-based rendering coordinated with depth information. In Image Analysis - 15th Scandinavian Conference, SCIA 2007, Proceedings. 2007. p. 193-202. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Hori, Maiya ; Kanbara, Masayuki ; Yokoya, Naokazu. / Novel stereoscopic view generation by image-based rendering coordinated with depth information. Image Analysis - 15th Scandinavian Conference, SCIA 2007, Proceedings. 2007. pp. 193-202 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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