Conference paper
3D-Div: A novel local surface descriptor for feature matching and pairwise range image registration
2013 IEEE International Conference on Image Processing
IEEE International Conference on Image Processing 2013 (Melbourne, VIC, 15/09/2013–18/09/2013)
2013
Abstract
This paper presents a novel local surface descriptor, called 3D-Div. The proposed descriptor is based on the concept of 3D vector fields divergence, extensively used in electromagnetic theory. To generate a 3D-Div descriptor of a 3D surface, a keypoint is first extracted on the 3D surface, then a local patch of a certain size is selected around that keypoint. A Local Reference Frame (LRF) is then constructed at the keypoint using all points forming the patch. A normalized 3D vector field is then computed at each point in the patch and referenced with LRF vectors. The 3D-Div descriptors are finally generated as the divergence of the reoriented 3D vector field. We tested our proposed descriptor on the low resolution Washington RGB-D (Kinect) object dataset. Performance was evaluated for the tasks of feature matching and pairwise range image registration. Experimental results showed that the proposed 3D-Div is 88% more computationally efficient and 47% more accurate than commonly used Spin Image (SI) descriptors.
Details
- Title
- 3D-Div: A novel local surface descriptor for feature matching and pairwise range image registration
- Authors/Creators
- S.A.A. Shah (Author/Creator)M. Bennamoun (Author/Creator)F. Boussaid (Author/Creator)A.A. El-Sallam (Author/Creator)
- Publication Details
- 2013 IEEE International Conference on Image Processing
- Conference
- IEEE International Conference on Image Processing 2013 (Melbourne, VIC, 15/09/2013–18/09/2013)
- Identifiers
- 991005540888507891
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Conference paper
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