Authors:
Kenta Suzuki
;
Fumihiko Sakaue
and
Jun Sato
Affiliation:
Nagoya Institute of Technology, Japan
Keyword(s):
3D Object Recognition, 3D Invariants, Projector-camera Systems, Coded-projection.
Related
Ontology
Subjects/Areas/Topics:
Active and Robot Vision
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Shape Representation and Matching
;
Stereo Vision and Structure from Motion
Abstract:
In this paper, we propose a method for computing stable 3D features for 3D object recognition. The feature is projective invariant computed from 3D information which is based on disparity of two projectors. In our method, the disparity can be estimated just from image intensity without obtaining any explicit corresponding points. Thus, we do not need any image matching method in order to obtain corresponding points. This means
that we can avoid any kind of problems arise from image matching essentially. Therefore, we can compute 3D invariant features from the 3D information reliably. The experimental results show our proposed invariant feature is useful for 3D object recognition.