ACM Home Page
Please provide us with feedback. Feedback
Adaptive camera calibration in an industrial robotic environment
Full text PdfPdf (568 KB)
Source International conference on Industrial and engineering applications of artificial intelligence and expert systems archive
Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 1 table of contents
Charleston, South Carolina, United States
Pages: 242 - 251  
Year of Publication: 1990
ISBN:0-89791-372-8
Authors
Michael Magee  Computer Science Department, University of Wyoming, P.O. Box 3682, Laramie, Wyoming
William Hoff  Martin Marietta Astronautics Group, M.S. 4372, P.O. Box 179, Denver, Colorado
Lance Gatrell  Martin Marietta Astronautics Group, M.S. 4372, P.O. Box 179, Denver, Colorado
Martin Marietta
William Wolfe  Department of Computer Science and Electrical Engineering, University of Colorado at Denver, 1200 North Larimer Street, Denver, Colorado
Sponsor
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 1,   Downloads (12 Months): 11,   Citation Count: 1
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues   peer to peer  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/98784.98825
What is a DOI?

ABSTRACT

One of the fundamental difficulties that arises when attempting to use computer vision in dynamic environments is that camera calibration coefficients must be adjusted as the relative distances between camera and target object change, causing refocusing to occur. Such situations arise frequently in robotic environments in which the visual sensor is mobile or the target objects are in motion. This paper presents a method for computing camera calibration coefficients for cases in which it is known that the relative motion between camera and target object is a translation along the optical axis, as in cases for which the camera is moving directly toward or away from an object of interest. The calibration technique is straightforward, involving only the solution of linear equations. It is demonstrated that, within the context of a spatial reasoning system, inclusion of the calibration method can improve the relative accuracy of spatial inferences by one to two orders of magnitude.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
R. O. Duda and P.E. Hart, Pattern Classification and Scene Analysis, Wiley-Interscience, 1972, pp. 392-393, 436-431.
 
2
 
3
H. Itoh, A. Miyauchiand S. Ozawa, "Distance Measuring Method Using only Simple Vision Constructed for Moving Robots", Proceedings of the IEEE 7th International Co nference o n Pattern Recognition, Montreal, Canada, 1984, pp. 192-195.
 
4
5
 
6
Y. Hung, P. Yeh and D. Harwood, "Passive Ranging To Known Planar Point Sets", Proceedings of the IEEE International Conference On Robotics And Automation, St. Louis, Missouri, March 25-28, 1985.


Collaborative Colleagues:
Michael Magee: colleagues
William Hoff: colleagues
Lance Gatrell: colleagues
Martin Marietta: colleagues
William Wolfe: colleagues

Peer to Peer - Readers of this Article have also read: