Citation
Rahmita Wirza O.K
(2018)
A method for estimating three-dimensional depth value from two-dimensional images.
PC:T/MY2017/050057.
Abstract
The present invention relates to a method for estimating three-dimensional depth value from two-dimensional images, characterised by the steps of placing an object (102) on a rotatable plate (103); acquiring a first view of the object (102) comprising a first image and a second image of the object (102), wherein the first image of the object (102) is captured at an angle between 0° to 360°, and the second image is captured at an angle in a range of 1° to 35° relative to the first image; obtaining two-dimensional feature point coordinates by applying Good Features to Track technique and extracting colour information, simultaneously, from the first image and the second image; filtering two-dimensional feature point coordinates; applying Pyramidal Lucas-Kanade Optical Flow technique to obtain displacement magnitudes from the two-dimensional feature point coordinates; calculating World Coordinate; estimating the three-dimensional depth value of the acquired images; and implementing inverse perspective mapping algorithm on the three-dimensional feature point coordinates.
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Additional Metadata
| Item Type: |
Patent
|
| Subject: |
Computer Vision |
| Subject: |
Computer Graphics |
| Subject: |
Information Technology |
| Application Number: |
PC:T/MY2017/050057 |
| Filing Date: |
2017-09-14 |
| Divisions: |
Faculty of Computer Science and Information Technology |
| Keywords: |
3D depth estimation; 2D images; object rotation; stereo vision; feature point extraction; Good Features to Track; Pyramidal Lucas-Kanade Optical Flow; world coordinate calculation; inverse perspective mapping; 3D reconstruction |
| Sustainable Development Goals (SDGs): |
SDG 9: Industry, Innovation and Infrastructure, SDG 11: Sustainable Cities and Communities, SDG 12: Responsible Consumption and Production |
| Depositing User: |
Ms. Nur Aina Ahmad Mustafa
|
| Date Deposited: |
01 Jul 2026 01:54 |
| Last Modified: |
01 Jul 2026 01:54 |
| URI: |
http://psasir.upm.edu.my/id/eprint/126718 |
| Statistic Details: |
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