Multi-view stereo ranging via Distributed Ray Tracing

We explore the use of Distributed Ray Tracing (DRT), an anti-aliasing technique from computer graphics, in multi-view computational stereo. As an example, we study ABM, a multi-view stereo algorithm based on a set of Hough transform accumulation operations. Augmenting ABM with DRT improves both internal signal quality and reconstruction accuracy. Results are given for both fundamental and complex “super-resolution reconstruction” tasks, where the voxel side length is less than the image ground sample distance. DRT improves ABM accuracy by 18% and can be generalized to improve other stereo algorithms.

[1]  Robert L. Cook,et al.  Distributed ray tracing , 1984, SIGGRAPH.

[2]  Josef Kittler,et al.  A survey of the hough transform , 1988, Comput. Vis. Graph. Image Process..

[3]  Josef Kittler,et al.  A comparison of Hough transform methods , 1989 .

[4]  Steven K. Feiner,et al.  Computer graphics: principles and practice (2nd ed.) , 1990 .

[5]  Alfred M. Bruckstein,et al.  Antialiasing the Hough transform , 1991, CVGIP Graph. Model. Image Process..

[6]  Shinjiro Kawato.  Hough Transform to Extract 3D Information from Images of Different View Points , 1993, CAIP.

[7]  Shiu Yin Yuen,et al.  An analysis on quantizing the hough space , 1994, Pattern Recognit. Lett..

[8]  M. Carter.  Computer graphics: Principles and practice , 1997 .

[9]  Thomas Ertl,et al.  Computer Graphics - Principles and Practice, 3rd Edition , 2014 .

[10]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[11]  Kiriakos N. Kutulakos,et al.  A Theory of Shape by Space Carving , 2000, International Journal of Computer Vision.

[12]  Dragutin Petkovic,et al.  On improving the accuracy of the Hough transform , 2005, Machine Vision and Applications.

[13]  Richard Szeliski,et al.  A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[14]  Alan C. Bovik,et al.  Efficient Stereoscopic Ranging via Stochastic Sampling of Match Quality , 2010, IEEE Transactions on Image Processing.