3D Scanner from Two Web Cameras

Authors

  • Aram V. Gevorgyan Russian-Armenian University
  • Hakob G. Sarukhanyan Institute for Informatics and Automation Problems of NAS RA

Keywords:

Stereovision, Depth map, Registration, ICP, 3D model

Abstract

In this paper we present an approach how to build 3D scanner using two ordinary web cameras. This approach is based on stereovision and is beneficial from the other 3D scanners that it doesn’t need laser, structured light or other expensive sensors. We put the object in front of the cameras at a distance about 40-50 cm and rotate it at small degrees. For every rotation we compute the disparity map from two cameras and then get the depth map in the form of point cloud. Then we filter out our object from the scene and then merge object point clouds from different views to get a full 3D model.

References

P. Hillman, “White paper: Camera Calibration and Stereo Vision”, Lochrin Terrace, Edinburgh EH3 9QL, Tech. Rep, 2005.

Z. Zhang, “A flexible new technique for camera calibration”, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1330–1334, 2000.

Z. Zhang, "Camera calibration with one-dimensional objects", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, pp. 892-899, 2004.

Epipolar Geometry tutorial. [Online]. Available: http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/OWENS/LECT10/node3. html

H. Hirschmuller, “Accurate and Efficient Stereo Processing by Semi Global Matching and Mutual Information.” IEEE Computer Vision and Pattern Recognition, vol. 2, pp. 807-814 2005.

D. Scharstein and R. Szeliski, “A taxonomy and evaluation of dense two-frame stereo correspondence algorithms”, International Journal of Computer Vision, vol. 47, pp. 7-42, 2002.

P. J.Bagga, “Real time depth computation using stereo imaging”, Journal Electrical and Electronic Engineering, vol. 1, pp. 51-54, 2013.

M. A. Mahammed, A. I. Melhum and F. A. Kochery, “Object distance measurement by stereo vision”, International Journal of Science and Applied Information Technology, vol. 2, pp. 05-08, March 2013.

P. J. Besl and H. D. Mckay, “A method for registration of 3-Dshapes”, IEEE Trans. Pattern Anal. Mach. Intell., pp. 239–256, 1992.

S. Rusinkiewicz and M. Levoy, “Efficient variants of the ICP algorithm”, 3-D Digital Imaging and Modeling, pp. 145–152, 2001.

A. Johnson and S. Kang, “Registration and integration of textured 3D data”, In Proc. 3DIM ’97, Ottawa, pp. 234–241, 1997.

G. Bradski and A. Kaehler, Learning OpenCV: Computer Vision with the OpenCV Library, 1st ed., O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, 2008.

The OpenCV website. [Online]. Available: http://opencv.org/

The Point Cloud Library website. [Online]. Available: http://pointclouds.org/

Z. Lv and Z. Zhang, "Build 3D Scanner System based on Binocular Stereo Vision", Journal of Computers, vol. 7., No 2, February 2012.

Tzung-Han Lin, "Resolution adjustable 3D scanner based on using stereo cameras", Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013 Asia-Pacific, 2013.

M. Pashaei, S. M. Mousavi, "Implementation of a low cost structured light scanner", Int. ch. Photogramm. Remote Sens. Spatial Inf. Sci., vol. XL-5/W2., pp.477-482, 2013.

Downloads

Published

2021-12-10

How to Cite

Gevorgyan , A. V. ., & Sarukhanyan, H. G. . (2021). 3D Scanner from Two Web Cameras. Mathematical Problems of Computer Science, 44, 42–50. Retrieved from http://mpcs.sci.am/index.php/mpcs/article/view/181