An information theoretic approach for next best view planning in 3-D reconstruction
Wenhardt S, Deutsch B, Hornegger J, Niemann H, Denzler J (2006)
Publication Type: Conference contribution, Conference Contribution
Publication year: 2006
Journal
Original Authors: Wenhardt S., Deutsch B., Hornegger J., Niemann H., Denzler J.
Book Volume: 1
Pages Range: 103-106
Event location: Hong Kong
Journal Issue: null
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.
Authors with CRIS profile
Stefan Wenhardt
Technische Fakultät
Joachim Hornegger
Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung)
Heinrich Niemann
Technische Fakultät
Involved external institutions
Germany (DE)How to cite
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.
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