Abstract
We propose a new computational model that accounts for human perception of depth for “ambiguous regions,” in which no information exists to estimate binocular disparity as seen in black and white papers. Random dot stereograms are widely used examples because these patterns provide sufficient information for disparity calculation. Then, a simple question confronts us: “how can we estimate the depth of non-textured images, like those on white paper?” In such non-textured regions, mathematical solutions of the spatial disparities are not unique but indefinite. We examine a mathematical description of depth estimation that is consistent with psychological experiments for non-textured images. Using computer simulation, we show that resultant depth-maps using our model based on the mathematical description above qualitatively reproduce human depth perception.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Mark, A.G., Yates, T.A., Schofield, A.J.: Depth propagation and surface construction in 3-D vision. Vision Research 49, 84–95 (2009)
Belhumeur, P.N.: A Bayesian approach to binocular stereopsis. International Journal of Computer Vision 19, 237–262 (1996)
Ishikawa, H.: Total Absolute Gaussian Curvature for Stereo Prior. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds.) ACCV 2007, Part II. LNCS, vol. 4844, pp. 537–548. Springer, Heidelberg (2007)
Ishikawa, H., Geiger, D.: Illusory volumes in human stereo perception. Vision Research 46(1-2), 171–178 (2006)
Satoh, S., Usui, S.: Computational theory and applications of a filling-in process at the blind spot. Neural Networks 21, 1261–1271 (2008)
Bertalmio, M., Sapiro, G., Caselles, V., Ballester, C.: Image inpainting. In: Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques – SIGGRAPH 2000, pp. 417–424 (2000)
Satoh, S.: Computational identity between digital image inpainting and filling-in process at the blind spot. Neural Computing and Applications 21, 613–621 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mitsukura, E., Satoh, S. (2013). Computational Study of Depth Perception for an Ambiguous Image Region: How Can We Estimate the Depth of Black or White Paper?. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8228. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42051-1_29
Download citation
DOI: https://doi.org/10.1007/978-3-642-42051-1_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-42050-4
Online ISBN: 978-3-642-42051-1
eBook Packages: Computer ScienceComputer Science (R0)