Influence of Temperature Variations on Calibrated Cameras
The camera parameters are changed due to temperature
variations, which directly influence calibrated cameras accuracy.
Robustness of calibration methods were measured and their accuracy
was tested. An error ratio due to camera parameters change
with respect to total error originated during calibration process was
determined. It pointed out that influence of temperature variations
decrease by increasing distance of observed objects from cameras.
[1] David A. Forsyth and Jean Ponce. Computer Vision - A Modern
Approach. Prentice Hall, August 2002. 693 pp.
[2] Richard Hartley and Andrew Zisserman. Multiple View Geometry in
Computer Vision. Cambridge University Press and ISBN: 0521540518,
second edition, 2004.
[3] Richard I. Hartley. In defense of the eight-point algorithm. IEEE
Transactions on pattern analysis and machine intelligence, 19(6):580-
593, June 1997.
[4] Timo Kahlmann, Fabio Remondino, and H. Ingensand. Calibration
for increased accuracy of the range imaging camera swissrangerTM.
In SPRS Commission V Symposium -Image Engineering and Vision
Metrology-, volume XXXVI, pages 136-141, Dresden, 25-27 September
2006.
[5] Jeffrey C. Lagarias, James A. Reeds, Margaret H. Wright, and Paul E.
Wright. Convergence properties of the Nelder Mead simplex method in
low dimensions. SIAM Journal of Optimization, 9(1):112-147, 1998.
[6] Peter Podbreznik and Božidar Poto╦çcnik. Analytical camera model
supplemented with influence of temperature variations. In CVISP 2008
Conference, submitted, Prague, Czech Republic, July 2008.
[7] Peter Podbreznik and Danijel Rebolj. Automatic comparison of site
images and the 4D model of the buiding. In Scherer Raimar J.,
Katranuschkov Peter, and Schapke Sven-Eric, editors, CIB W78 22nd
conference on information technology in construction, pages 235-239,
Dresden, Germany, july 2005. Institute for Construction Informatics and
Technische Universitat and Dresden.
[8] Peter Podbreznik and Danijel Rebolj. Building elements recognition using
site images and 4D model. In Hugues Rivard; Edmond Miresco and
Hani Melhem, editors, Joint international conference on computing and
decision making in civil and building engineering, page 87, Montreal,
Canada, june 2006.
[9] Thierry Sentenac, Yannick Le Maoultt, Guy Rolland, and Michel Devy.
Temperature correction of radiometric and geometric models for an
uncooled CCD camera in the near infrared. IEEE Transactions on
instrumentation and measurement, 52(1):46-60, February 2003.
[10] Zhengyou Zhang. Parameter estimation techniques: A tutorial with
application to conic fitting. Technical Report 2676, Institut National
de Recherche en Informatique et en Automatique, October 1995.
[11] Zhengyou Zhang. Determining the epipolar geometry and its uncertainty:
A review. International Journal of Computer Vision, 2(27):161-
198, 1998.
[1] David A. Forsyth and Jean Ponce. Computer Vision - A Modern
Approach. Prentice Hall, August 2002. 693 pp.
[2] Richard Hartley and Andrew Zisserman. Multiple View Geometry in
Computer Vision. Cambridge University Press and ISBN: 0521540518,
second edition, 2004.
[3] Richard I. Hartley. In defense of the eight-point algorithm. IEEE
Transactions on pattern analysis and machine intelligence, 19(6):580-
593, June 1997.
[4] Timo Kahlmann, Fabio Remondino, and H. Ingensand. Calibration
for increased accuracy of the range imaging camera swissrangerTM.
In SPRS Commission V Symposium -Image Engineering and Vision
Metrology-, volume XXXVI, pages 136-141, Dresden, 25-27 September
2006.
[5] Jeffrey C. Lagarias, James A. Reeds, Margaret H. Wright, and Paul E.
Wright. Convergence properties of the Nelder Mead simplex method in
low dimensions. SIAM Journal of Optimization, 9(1):112-147, 1998.
[6] Peter Podbreznik and Božidar Poto╦çcnik. Analytical camera model
supplemented with influence of temperature variations. In CVISP 2008
Conference, submitted, Prague, Czech Republic, July 2008.
[7] Peter Podbreznik and Danijel Rebolj. Automatic comparison of site
images and the 4D model of the buiding. In Scherer Raimar J.,
Katranuschkov Peter, and Schapke Sven-Eric, editors, CIB W78 22nd
conference on information technology in construction, pages 235-239,
Dresden, Germany, july 2005. Institute for Construction Informatics and
Technische Universitat and Dresden.
[8] Peter Podbreznik and Danijel Rebolj. Building elements recognition using
site images and 4D model. In Hugues Rivard; Edmond Miresco and
Hani Melhem, editors, Joint international conference on computing and
decision making in civil and building engineering, page 87, Montreal,
Canada, june 2006.
[9] Thierry Sentenac, Yannick Le Maoultt, Guy Rolland, and Michel Devy.
Temperature correction of radiometric and geometric models for an
uncooled CCD camera in the near infrared. IEEE Transactions on
instrumentation and measurement, 52(1):46-60, February 2003.
[10] Zhengyou Zhang. Parameter estimation techniques: A tutorial with
application to conic fitting. Technical Report 2676, Institut National
de Recherche en Informatique et en Automatique, October 1995.
[11] Zhengyou Zhang. Determining the epipolar geometry and its uncertainty:
A review. International Journal of Computer Vision, 2(27):161-
198, 1998.
@article{"International Journal of Electrical, Electronic and Communication Sciences:56372", author = "Peter Podbreznik and Božidar Potocnik", title = "Influence of Temperature Variations on Calibrated Cameras", abstract = "The camera parameters are changed due to temperature
variations, which directly influence calibrated cameras accuracy.
Robustness of calibration methods were measured and their accuracy
was tested. An error ratio due to camera parameters change
with respect to total error originated during calibration process was
determined. It pointed out that influence of temperature variations
decrease by increasing distance of observed objects from cameras.", keywords = "camera calibration, perspective projection matrix,
epipolar geometry, temperature variation.", volume = "2", number = "5", pages = "844-7", }
