Abstract
We propose a stereo camera self-adjustment methodology based on a correlation algorithm. We focus on stereo cameras in vision systems for vehicles and Unmanned Aerial Vehicles. We therefore focus on changes of vergence angle. Our approach uses the following methodology: (1) feature detection using an edge density image, (2) stereo matching to find the lost camera parameters, and (3) a self-adjustment procedure. We have confirmed that a combination of these procedures recovers the camera parameters by using the textured features typical of outdoor environments, even if parameters are lost because of a change of vergence angle.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - Digital Image Computing: Techniques and Applications, DICTA 2008 |
| Pages | 428-435 |
| Number of pages | 8 |
| DOIs | |
| Publication status | Published - 2008 |
| Externally published | Yes |
| Event | Digital Image Computing: Techniques and Applications, DICTA 2008 - Canberra, ACT Duration: 2008 Dec 1 → 2008 Dec 3 |
Other
| Other | Digital Image Computing: Techniques and Applications, DICTA 2008 |
|---|---|
| City | Canberra, ACT |
| Period | 08/12/1 → 08/12/3 |
Fingerprint
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Computer Science Applications
Cite this
A stereo self-adjustment methodology for camera parameter restoration in outdoor environments. / Nakagawa, Masafumi; Yoshihiro, Kawai; Fumiaki, Tomita.
Proceedings - Digital Image Computing: Techniques and Applications, DICTA 2008. 2008. p. 428-435 4700053.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A stereo self-adjustment methodology for camera parameter restoration in outdoor environments
AU - Nakagawa, Masafumi
AU - Yoshihiro, Kawai
AU - Fumiaki, Tomita
PY - 2008
Y1 - 2008
N2 - We propose a stereo camera self-adjustment methodology based on a correlation algorithm. We focus on stereo cameras in vision systems for vehicles and Unmanned Aerial Vehicles. We therefore focus on changes of vergence angle. Our approach uses the following methodology: (1) feature detection using an edge density image, (2) stereo matching to find the lost camera parameters, and (3) a self-adjustment procedure. We have confirmed that a combination of these procedures recovers the camera parameters by using the textured features typical of outdoor environments, even if parameters are lost because of a change of vergence angle.
AB - We propose a stereo camera self-adjustment methodology based on a correlation algorithm. We focus on stereo cameras in vision systems for vehicles and Unmanned Aerial Vehicles. We therefore focus on changes of vergence angle. Our approach uses the following methodology: (1) feature detection using an edge density image, (2) stereo matching to find the lost camera parameters, and (3) a self-adjustment procedure. We have confirmed that a combination of these procedures recovers the camera parameters by using the textured features typical of outdoor environments, even if parameters are lost because of a change of vergence angle.
UR - http://www.scopus.com/inward/record.url?scp=67649127049&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67649127049&partnerID=8YFLogxK
U2 - 10.1109/DICTA.2008.103
DO - 10.1109/DICTA.2008.103
M3 - Conference contribution
AN - SCOPUS:67649127049
SN - 9780769534565
SP - 428
EP - 435
BT - Proceedings - Digital Image Computing: Techniques and Applications, DICTA 2008
ER -