|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 119 - Issue 15 |
| Published: June 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 },
year = { 2015 },
volume = { 119 },
number = { 15 },
pages = { 27-32 },
doi = { 10.5120/21144-4199 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2015
%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%T
%J International Journal of Computer Applications
%V 119
%N 15
%P 27-32
%R 10.5120/21144-4199
%I Foundation of Computer Science (FCS), NY, USA
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.