Recognizing 3D Objects for 2D Images: An Error Analysis
Abstract
Many recent object recognition systems use a small number of pairings of data and model features to compute the three-dimensional transformation from a model coordinate frame into the sensor coordinate system. In the case of perfect image data, these systems seem to work well. With uncertain image data, however, the performance of such methods is less well understood. In this paper, the authors examine the effects of two-dimensional sensor uncertainty on the computation of three-dimensional model transformations. They use this analysis to bound the uncertainty in the transformation parameters as well as the uncertainty associated with applying the transformation to map other model features into the image. They also examine the effects of the transformation uncertainty on the effectiveness of recognition methods.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 1992
- Accession Number
- ADA260150
Entities
People
- Daniel P. Huttenlocher
- T. D. Alter
- W. E. Grimson
Organizations
- Massachusetts Institute of Technology