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Reseach Article

An Approach to Calculate Depth of an Object in a 2-D Image and Map it into 3-D Space

by Ashis Pradhan, Ashit Kr. Singh, Shubhra Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 15
Year of Publication: 2015
Authors: Ashis Pradhan, Ashit Kr. Singh, Shubhra Singh
10.5120/21144-4199

Ashis Pradhan, Ashit Kr. Singh, Shubhra Singh . An Approach to Calculate Depth of an Object in a 2-D Image and Map it into 3-D Space. International Journal of Computer Applications. 119, 15 ( June 2015), 27-32. DOI=10.5120/21144-4199

@article{ 10.5120/21144-4199,
author = { Ashis Pradhan, Ashit Kr. Singh, Shubhra Singh },
title = { An Approach to Calculate Depth of an Object in a 2-D Image and Map it into 3-D Space },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 15 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 27-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number15/21144-4199/ },
doi = { 10.5120/21144-4199 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:04:08.477927+05:30
%A Ashis Pradhan
%A Ashit Kr. Singh
%A Shubhra Singh
%T An Approach to Calculate Depth of an Object in a 2-D Image and Map it into 3-D Space
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 15
%P 27-32
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The essence of an image is a projection from a 3-D scene onto a 2-D plane, during which the depth information is lost. The 3-D point corresponding to a specific image point is constrained to be on the line of sight. From a single image, it is very difficult to determine the depth information of various object points in an image. If two or more 2-D images are used, then the relative depth point of the image points can be calculated which can be further used to reconstruct the 3-D image by projecting the image points which includes the depth information as well. This paper presents two techniques namely binocular disparity and photometric stereo for depth calculation and 3-D reconstruction of an object in an image as it requires minimum user intervention. Binocular disparity method requires a pair of stereo images to compute disparity and depth to generate the desired 3-D view whereas the photometric stereo method requires multiple images under different light directions.

References
  1. Han, F. and Zhu, S. C. , "Bayesian Reconstruction of 3-D shapes and scenes from a single image". Proceeding of the first IEEE International Workshop on Higher Level knowledge in 3-D Modeling and Motion Analysis. 2003
  2. Rother, D. , Patwardhan, K. , Aganj, I. and Sapiro, G. , "3-D Priors for Scene Learning from a Single View. " S3-D Workshop (at Proc. IEEE Int'l Conf. Computer Vision and Pattern Recognition). 2008.
  3. Ted Shultz and Luis A. Rodriguez, "3-D Reconstruction from two 2-D images", ECE 533 Fall 2003.
  4. Sebastian Roy and Ingemar Cox. A maximum-?ow formulation of the n-camera stereo correspondence problem. In IEEE Proc. of Int. Conference on Computer Vision, pages 492–499, 1998.
  5. Lee Sang-Hyun, Park Dae-Won, Jeong Je-Pyong and Moon Kyung-Il, "Conversion 2-D Image to 3-D Based on Squeeze function and Gradient Map", International Journal of Software Engineering and Its Applications Vol. 8, No. 2, 2014.
  6. Arne Henrichsen, "3-D Reconstruction and Camera Calibration from 2-D Images", Department of Electrical Engineering, University of Cape Town, December 2000.
  7. Assoc. Prof. Dr. Ir. E. A. Hendriks Dr. Ir. P. A. Redert, "Converting 2-D to 3-D: A Survey", Information and Communication Theory Group (ICT) Faculty of Electrical Engineering, Mathematics and Computer Science Delft University of Technology, the Netherlands, December 2005.
  8. Rashmi, Mukesh Kumar, Rohit Saxena, "Algorithm and Technique on Various Edge Detection: A Survey", Signal & Image Processing: An International Journal (SIPIJ) Vol. 4, No. 3, June 2013.
  9. Robert J. Woodham, "Photometric method for determining surface orientation from multiple images", Department of Computer Science, University of British Columbia, Optical Engineering, 1980.
  10. Carlos Hernandez, George Vogiatzis, Roberto Cipolla, "Multi-View photometric stereo", Pattern Analysis and Machine Intelligence, IEEE Transactions, March 2008.
  11. Aaron Hertzmann, Steven M. Seitz, "Example-Based photometric stereo: Shape reconstruction with general, varying BRDFs", Pattern Analysis and Machine Intelligence, IEEE Transactions, Vol 27, August 2005.
  12. S. Barsky, "Surface Shape and Colour Reconstruction using Photometric Stereo", PhD thesis, School of Electronics and Physical Science, University of Surrey, UK, 2003.
  13. C. Hernandez, F. Schmitt, and R. Cipolla, "Silhouette coherence for camera calibration under circular motion," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 29, no. 2, pp. 343-349, Feb 2007.
  14. Hayakawa, Hideki. "Photometric stereo under a light source with arbitrary motion. " Journal of the Optical Society of America, 1994. Available online at http://pages. cs. wise. edu%7Ecs7661/projects/phs/hayakawa. pdf
  15. Zhang, R. ; Tsai, P. ; Cryer, J. E. ; Shah, M. (1999), "Shape from Shading: A Survey", IEEE Transactions on Pattern Analysis and Machine Intelligence archive, Vol. 21, Issue 8, Pages: 690-706.
  16. Ning Qian, " Binocular Disparity and perception of Depth. ", Center for Neurobiology and Behavior Columbia University, Neuron, Vol. 18, 359-368,March 1997.
  17. Seitz, Steven. "Computer Vision (CSEP 576), Winter 2005 - Project 3: Photometric Stereo. " Available online at: http://www. cs. washington. edu/education/courses/csep576/05wi/projects/project3/project3. htm
  18. Adam Bechle. "Computer Vision (CS 766),2008 Project 3: Photometric Stereo" Available online at http://pages. cs. wisc. edu/~lizhang/courses/cs766-2008f/projects/phs/students/bechle/website. html
  19. Dr. SukhenduDas. "Computer Vision (CS 635 ), Shape from Shading. " Available online at http://www. cse. iitm. ac. in/~vplab/courses/CV_DIP/PDF/ShapeFromShading. pdf
Index Terms

Computer Science
Information Sciences

Keywords

Feature point Binocular disparity Edge detection Depth Photometric stereo Normal map Highlight.