OSA's Digital Library

Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 8, Iss. 2 — Mar. 4, 2013

Depth estimation for speckle projection system using progressive reliable points growing matching

Guijin Wang, Xuanwu Yin, Xiaokang Pei, and Chenbo Shi  »View Author Affiliations


Applied Optics, Vol. 52, Issue 3, pp. 516-524 (2013)
http://dx.doi.org/10.1364/AO.52.000516


View Full Text Article

Enhanced HTML    Acrobat PDF (2209 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

In this paper, we propose a progressive reliable points growing matching scheme to estimate the depth from the speckle projection image. First a self-adapting binarization is introduced to reduce the influence of inconsistent intensity. Then we apply local window-based correlation matching to get the initial disparity map. After the initialization, we formulate a progressive updating scheme to update the disparity estimation. There are two main steps in each round of updation. At first new reliable points are progressively selected based on three aspects of criterion including matching degree, confidence, and left–right consistency; then prediction-based growing matching is adopted to recalculate the disparity map from the reliable points. Finally, the more accurate depth map can be obtained by subpixel interpolation and transformation. The experimental results well demonstrate the effectiveness and low computational cost of our scheme.

© 2013 Optical Society of America

OCIS Codes
(150.6910) Machine vision : Three-dimensional sensing
(330.1400) Vision, color, and visual optics : Vision - binocular and stereopsis

ToC Category:
Vision, Color, and Visual Optics

History
Original Manuscript: July 31, 2012
Revised Manuscript: October 23, 2012
Manuscript Accepted: November 14, 2012
Published: January 18, 2013

Virtual Issues
Vol. 8, Iss. 2 Virtual Journal for Biomedical Optics

Citation
Guijin Wang, Xuanwu Yin, Xiaokang Pei, and Chenbo Shi, "Depth estimation for speckle projection system using progressive reliable points growing matching," Appl. Opt. 52, 516-524 (2013)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=ao-52-3-516


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. Y. Chen and B. Chen, “Measuring of a three-dimensional surface by use of a spatial distance computation,” Appl. Opt. 42, 1958–1972 (2003). [CrossRef]
  2. M. Schaffer, M. Grosse, and R. Kowarschik, “High-speed pattern projection for three-dimensional shape measurement using laser speckles,” Appl. Opt. 49, 3622–3629 (2010). [CrossRef]
  3. H. Dai and X. Su, “Shape measurement by digital speckle temporal sequence correlation with digital light projector,” Opt. Eng. 40, 793–800 (2001) (in Chinese). [CrossRef]
  4. B. Freedman, A. Shpunt, M. Machline, and Y. Arieli, “Depth mapping using projected patterns,” U.S. patent 0,118,123 (13May2010).
  5. A. Shpunt and Z. Zalevsky, “Three-dimensional sensing using speckle patterns,” U.S. patent 0,096,783 (16April2009).
  6. D. Scharstein and R. Szeliski, “A taxonomy and evaluation of dense two-frame stereo correspondence algorithms,” Int. J. Comput. Vis. 47, 7–42 (2002). [CrossRef]
  7. Q. Yang, L. Wang, R. Yang, H. Stewenius, and D. Nister, “Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion handling,” IEEE Trans. Pattern Anal. Mach. Intell. 31, 492–504 (2009). [CrossRef]
  8. C. Shi, G. Wang, X. Pei, B. He, and X. Lin, “An interleaving updating framework of disparity and confidence map for stereo matching,” IEICE Trans. Inf. Syst. E95-D, 1552–1555 (2012). [CrossRef]
  9. C. Shi, G. Wang, X. Pei, B. He, and X. Lin, “Stereo matching using local plane fitting in confidence-based support window,” IEICE Trans. Inf. Syst. E95-D, 699–702 (2012). [CrossRef]
  10. K. Muhlmann, D. Maier, J. Hesser, and R. Manner, “Calculating dense disparity maps from color stereo images, an efficient implementation,” Int. J. Comput. Vis. 47, 79–88 (2002). [CrossRef]
  11. I. Haller and S. Nedevschi, “Design of interpolation functions for sub-pixel accuracy stereo-vision systems,” IEEE Trans. Image Process. 21, 889–898 (2011). [CrossRef]
  12. R. Zahib and J. Woodfill, “Non-parametric local transforms for computing visual correspondence,” Proc. ECCV 801, 151–158 (1994). [CrossRef]
  13. K. Khoshelham and S. Elberink, “Accuracy and resolution of kinect depth data for indoor mapping applications,” Sensors 12, 1437–1454 (2012). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited