IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovery of Parametric Models from Range Images: The Case for Superquadrics with Global Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sensor Modeling, Probabilistic Hypothesis Generation, and Robust Localization for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
3-D Pose from 3 Points Using Weak-Perspective
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding Corresponding Points Based on Bayesian Triangulation
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Autonomous recognition: driven by ambiguity
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A Fast Method for Estimating the Uncertainty in the Location of Image Points in 3D Recognition
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Active Recognition: Using Uncertainty to Reduce Ambiguity
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Estimating pose through local geometry
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
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We propose a the use of a consistent Bayesian methodology for the analysis of the uncertainty associated with a pose estimation procedure. A novel model-based technique to estimate the pose of rigid 3-D objects from laser range finder images is studied, and various sources of uncertainty are carried through the process using a Bayesian MAP treatment, yielding local, point-by-point estimates of position and predicted error. Promising experimental results on complex objects are presented and discussed.