An information theoretic approach for next best view planning in 3-D reconstruction

Beitrag bei einer Tagung
(Konferenzbeitrag)


Details zur Publikation

Autor(en): Wenhardt S, Deutsch B, Hornegger J, Niemann H, Denzler J
Jahr der Veröffentlichung: 2006
Band: 1
Heftnummer: null
Seitenbereich: 103-106
ISSN: 1051-4651


Abstract


We present an algorithm for optimal view point selection for 3-D reconstruction of an object using 2-D image points. Since the image points are noisy, a Kalman filter is used to obtain the best estimate of the object's geometry. This Kalman filter allows us to efficiently predict the effect of any given camera position on the uncertainty, and therefore quality, of the estimate. By choosing a suitable optimization criterion, we are able to determine the camera positions which minimize our reconstruction error. We verify our results using two experiments with real images: one experiment uses a calibration pattern for comparison to a ground-truth state, the other reconstructs a real world object. © 2006 IEEE.



FAU-Autoren / FAU-Herausgeber

Hornegger, Joachim Prof. Dr.-Ing.
Lehrstuhl für Informatik 5 (Mustererkennung)
Niemann, Heinrich Prof. Dr.
Technische Fakultät
Wenhardt, Stefan
Technische Fakultät


Autor(en) der externen Einrichtung(en)
Friedrich-Schiller-Universität Jena


Zitierweisen

APA:
Wenhardt, S., Deutsch, B., Hornegger, J., Niemann, H., & Denzler, J. (2006). An information theoretic approach for next best view planning in 3-D reconstruction. In Proceedings of the 18th International Conference on Pattern Recognition, ICPR 2006 (pp. 103-106). Hong Kong.

MLA:
Wenhardt, Stefan, et al. "An information theoretic approach for next best view planning in 3-D reconstruction." Proceedings of the 18th International Conference on Pattern Recognition, ICPR 2006, Hong Kong 2006. 103-106.

BibTeX: 

Zuletzt aktualisiert 2019-18-04 um 21:53