A computational model for perception of stereoscopic window violations

Creating a computational model for stereoscopic 3D perception is a highly complex undertaking. As one step towards this goal, this paper investigates stereoscopic window violation artifacts, which often interfere with artistic freedom and constrain the comfortable depth volume. Window violations need to be compensated for in most 3D feature movies. Currently this is done in an ad-hoc manner due to a limited understanding of the problem. In this work, we present a model predicting problematic window violations that are visually disturbing. The model parameters were defined through psychophysical experiments on simple stimuli. Then the model was calibrated and validated on real, complex stereoscopic images. Finally, we present a system to provide visualization of problematic stereoscopic window violations as well as details for how to correct them.

[1]  G. J. Mitchison,et al.  Interpolation in stereoscopic matching , 1985, Nature.

[2]  Hans-Peter Seidel,et al.  Video quality assessment for computer graphics applications , 2010, ACM Trans. Graph..

[3]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[4]  E. Peli.  Contrast in complex images. , 1990, Journal of the Optical Society of America. A, Optics and image science.

[5]  Wolfgang Heidrich,et al.  HDR-VDP-2: a calibrated visual metric for visibility and quality predictions in all luminance conditions , 2011, SIGGRAPH 2011.

[6]  Robert Neuman,et al.  Bolt 3D: a case study , 2009, Electronic Imaging.

[7]  J. Mayhew,et al.  Contrast Sensitivity Function for Stereopsis , 1978, Perception.

[8]  J A Solomon,et al.  Model of visual contrast gain control and pattern masking. , 1997, Journal of the Optical Society of America. A, Optics, image science, and vision.

[9]  D Marr,et al.  A computational theory of human stereo vision. , 1979, Proceedings of the Royal Society of London. Series B, Biological sciences.

[10]  Andrew B. Watson,et al.  The cortex transform: rapid computation of simulated neural images , 1987 .

[11]  Peter Eisert,et al.  The Stereoscopic Analyzer — An image-based assistance tool for stereo shooting and 3D production , 2010, 2010 IEEE International Conference on Image Processing.

[12]  Hans-Peter Seidel,et al.  New measurements reveal weaknesses of image quality metrics in evaluating graphics artifacts , 2012, ACM Trans. Graph..

[13]  Tomaso Poggio,et al.  Cooperative computation of stereo disparity , 1988 .

[14]  Bruce Walter,et al.  Visual equivalence: towards a new standard for image fidelity , 2007, ACM Trans. Graph..

[15]  Raymond Spottiswoode,et al.  The theory of stereoscopic transmission & its application to the motion picture , 1953 .

[16]  David M. Hoffman,et al.  The zone of comfort: Predicting visual discomfort with stereo displays. , 2011, Journal of vision.

[17]  Horst Bischof,et al.  Motion estimation with non-local total variation regularization , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  Aljoscha Smolic,et al.  Computational stereo camera system with programmable control loop , 2011, ACM Trans. Graph..

[19]  James E. Cutting,et al.  Chapter 3 – Perceiving Layout and Knowing Distances: The Integration, Relative Potency, and Contextual Use of Different Information about Depth* , 1995 .

[20]  Scott J. Daly,et al.  Visible differences predictor: an algorithm for the assessment of image fidelity , 1992, Electronic Imaging.

[21]  Y. Ohno.  CIE Fundamentals for Color Measurements , 2000, NIP & Digital Fabrication Conference.

[22]  K. Bala,et al.  Effects of global illumination approximations on material appearance , 2010, SIGGRAPH 2010.

[23]  David J. Sheskin,et al.  Handbook of Parametric and Nonparametric Statistical Procedures , 1997 .

[24]  Aljoscha Smolic,et al.  Nonlinear disparity mapping for stereoscopic 3D , 2010, ACM Trans. Graph..

[25]  Peter G. J. Barten,et al.  Contrast sensitivity of the human eye and its e ects on image quality , 1999 .

[26]  S. McKee,et al.  The role of retinal correspondence in stereoscopic matching , 1988, Vision Research.

[27]  Ben J Hicks,et al.  SPIE - The International Society for Optical Engineering , 2001 .

[28]  Hans-Peter Seidel,et al.  A perceptual model for disparity , 2011, ACM Trans. Graph..

[29]  Lenny Lipton,et al.  Foundations of the stereoscopic cinema : a study in depth , 1984 .

[30]  Rafael Monroy,et al.  Disparity-Aware Stereo 3D Production Tools , 2011, 2011 Conference for Visual Media Production.