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Author, Editor(s)

Author(s):

Vangorp, Peter
Richardt, Christian
Cooper, Emily A.
Chaurasia, Gaurav
Banks, Martin S.
Drettakis, George

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Not MPG Author(s):

Richardt, Christian
Cooper, Emily A.
Chaurasia, Gaurav
Banks, Martin S.
Drettakis, George

BibTeX cite key*:

Vangorp2013

Title

Title*:

Perception of Perspective Distortions in Image-Based Rendering


IBR_perception-paper.pdf (3215.62 KB)

Journal

Journal Title*:

ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH 2013)

Journal's URL:

http://tog.acm.org/

Download URL
for the article:

http://dl.acm.org/citation.cfm?id=2461971

Language:

English

Publisher

Publisher's
Name:

ACM

Publisher's URL:

http://www.acm.org/publications

Publisher's
Address:

New York, NY, USA

ISSN:

0730-0301

Vol, No, pp, Date

Volume*:

32

Number:

4

Publishing Date:

July 2013

Pages*:

58:1-12

Number of
VG Pages:


Page Start:


Page End:


Sequence Number:

58

DOI:

http://dx.doi.org/10.1145/2461912.2461971

Note, Abstract, ©

Note:


(LaTeX) Abstract:

Image-based rendering (IBR) creates realistic images by enriching simple geometries with photographs, e.g., mapping the photograph of a building façade onto a plane. However, as soon as the viewer moves away from the correct viewpoint, the image in the retina becomes distorted, sometimes leading to gross misperceptions of the original geometry. Two hypotheses from vision science state how viewers perceive such image distortions, one claiming that they can compensate for them (and therefore perceive scene geometry reasonably correctly), and one claiming that they cannot compensate (and therefore can perceive rather significant distortions). We modified the latter hypothesis so that it extends to street-level IBR. We then conducted a rigorous experiment that measured the magnitude of perceptual distortions that occur with IBR for façade viewing. We also conducted a rating experiment that assessed the acceptability of the distortions. The results of the two experiments were consistent with one another. They showed that viewers’ percepts are indeed distorted, but not as severely as predicted by the modified vision science hypothesis. From our experimental results, we develop a predictive model of distortion for street-level IBR, which we use to provide guidelines for acceptability of virtual views and for capture camera density. We perform a confirmatory study to validate our predictions, and illustrate their use with an application that guides users in IBR navigation to stay in regions where virtual views yield acceptable perceptual distortions.

URL for the Abstract:

http://www-sop.inria.fr/reves/Basilic/2013/VRCCBD13/

Categories,
Keywords:


HyperLinks / References / URLs:


Copyright Message:

Copyright ACM, 2013. This is the authors’ version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definite version was published in ACM TOG.

Personal Comments:


Download
Access Level:

Public

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Computer Graphics Group

External Affiliations:

REVES/INRIA Sophia-Antipolis; University of Giessen; University of California, Berkeley

Audience:

experts only

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort


BibTeX Entry:

@ARTICLE{Vangorp2013,
AUTHOR = {Vangorp, Peter and Richardt, Christian and Cooper, Emily A. and Chaurasia, Gaurav and Banks, Martin S. and Drettakis, George},
TITLE = {Perception of Perspective Distortions in Image-Based Rendering},
JOURNAL = {ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH 2013)},
PUBLISHER = {ACM},
YEAR = {2013},
NUMBER = {4},
VOLUME = {32},
PAGES = {58:1--12},
ADDRESS = {New York, NY, USA},
MONTH = {July},
ISBN = {0730-0301},
DOI = {http://dx.doi.org/10.1145/2461912.2461971},
}


Entry last modified by Peter Vangorp, 08/22/2014
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Editor(s)
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Created
01/14/2014 03:44:28 PM
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Editor(s)
Peter Vangorp
Peter Vangorp
Peter Vangorp

Edit Dates
08/22/2014 12:29:12 PM
01/14/2014 03:46:25 PM
01/14/2014 03:44:28 PM

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