Abstract
This research proposes a method to reconstruct the 3D object model from 2D images. The reconstruction theorem this research used is based on the stereo vision algorithm. Stereo vision is one type of the non-contact scanning measurement. The theorem of the stereo vision were simulates the human's eyes to calculate the object's depth information. There for, this research uses two CCD Cameras to capture the object's 2D images. Then find out the match points from the left and right two images. To reconstruct the object's 3D model by using the match points, parameters of the CCD Cameras and transform matrix that between the world coordinate and camera coordinate. The object this research reconstructed belongs to simple geometry. There for, we can reconstruct the object's 3D model by the feature points of the object. The feature points always appear on edges and vertices. In this way we can reduce the number of the points we should reconstruct, so the system can build up the object's 3D model fast. The CCD Cameras unable to capture the whole object's surface information in once time, so this research proposes a method that rotates the object to solve this problem. The system combines the rotation model with the reconstruction system to reconstruct the complete object's 3D model.
| Original language | English |
|---|---|
| Title of host publication | Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011 |
| Pages | 76-81 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2011 |
| Event | 2011 International Conference on System Science and Engineering, ICSSE 2011 - Macao, China Duration: 2011 Jun 8 → 2011 Jun 10 |
Other
| Other | 2011 International Conference on System Science and Engineering, ICSSE 2011 |
|---|---|
| Country | China |
| City | Macao |
| Period | 11/6/8 → 11/6/10 |
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Keywords
- 3D reconstruction
- Corner detection
- Stereo vision
ASJC Scopus subject areas
- Control and Systems Engineering
Cite this
3D object model recovery from 2D images utilizing corner detection. / Huang, Ying Yuan; Chen, Mei Yung.
Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011. 2011. p. 76-81 5961877.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - 3D object model recovery from 2D images utilizing corner detection
AU - Huang, Ying Yuan
AU - Chen, Mei Yung
PY - 2011
Y1 - 2011
N2 - This research proposes a method to reconstruct the 3D object model from 2D images. The reconstruction theorem this research used is based on the stereo vision algorithm. Stereo vision is one type of the non-contact scanning measurement. The theorem of the stereo vision were simulates the human's eyes to calculate the object's depth information. There for, this research uses two CCD Cameras to capture the object's 2D images. Then find out the match points from the left and right two images. To reconstruct the object's 3D model by using the match points, parameters of the CCD Cameras and transform matrix that between the world coordinate and camera coordinate. The object this research reconstructed belongs to simple geometry. There for, we can reconstruct the object's 3D model by the feature points of the object. The feature points always appear on edges and vertices. In this way we can reduce the number of the points we should reconstruct, so the system can build up the object's 3D model fast. The CCD Cameras unable to capture the whole object's surface information in once time, so this research proposes a method that rotates the object to solve this problem. The system combines the rotation model with the reconstruction system to reconstruct the complete object's 3D model.
AB - This research proposes a method to reconstruct the 3D object model from 2D images. The reconstruction theorem this research used is based on the stereo vision algorithm. Stereo vision is one type of the non-contact scanning measurement. The theorem of the stereo vision were simulates the human's eyes to calculate the object's depth information. There for, this research uses two CCD Cameras to capture the object's 2D images. Then find out the match points from the left and right two images. To reconstruct the object's 3D model by using the match points, parameters of the CCD Cameras and transform matrix that between the world coordinate and camera coordinate. The object this research reconstructed belongs to simple geometry. There for, we can reconstruct the object's 3D model by the feature points of the object. The feature points always appear on edges and vertices. In this way we can reduce the number of the points we should reconstruct, so the system can build up the object's 3D model fast. The CCD Cameras unable to capture the whole object's surface information in once time, so this research proposes a method that rotates the object to solve this problem. The system combines the rotation model with the reconstruction system to reconstruct the complete object's 3D model.
KW - 3D reconstruction
KW - Corner detection
KW - Stereo vision
UR - http://www.scopus.com/inward/record.url?scp=84860413821&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84860413821&partnerID=8YFLogxK
U2 - 10.1109/ICSSE.2011.5961877
DO - 10.1109/ICSSE.2011.5961877
M3 - Conference contribution
AN - SCOPUS:84860413821
SN - 9781612844718
SP - 76
EP - 81
BT - Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011
ER -