- Authors:
- DOI:
- 10.1109/ICRA.2013.6630856
- Abstract:
- We address the problem of estimating the alignment pose between two models using structure-specific local descriptors. Our descriptors are generated using a combination of 2D image data and 3D contextual shape data, resulting in a set of semi-local descriptors containing rich appearance and shape information for both edge and texture structures. This is achieved by defining feature space relations which describe the neighborhood of a descriptor. By quantitative evaluations, we show that our descriptors provide high discriminative power compared to state of the art approaches. In addition, we show how to utilize this for the estimation of the alignment pose between two point sets. We present experiments both in controlled and real-life scenarios to validate our approach.
- ISBN:
- 9781467356411
- Type:
- Conference paper
- Language:
- English
- Published in:
- Ieee International Conference on Robotics and Automation (icra), 2013, p. 2080-2087
- Main Research Area:
- Science/technology
- Publication Status:
- Published
- Review type:
- Peer Review
- Conference:
- 2013 IEEE International Conference on Robotics and Automation, 2013
- Publisher:
- IEEE
- Submission year:
- 2013
- Scientific Level:
- Scientific
- ID:
- 2185995178
0000-0002-6125-8481
Checking for on-site access...
