Authors:
Mahesh Kr. Singh
;
K. S. Venkatesh
and
Ashish Dutta
Affiliation:
Indian Institute of Technology Kanpur, India
Keyword(s):
Gaussian Mixture Model, Laser Range Scanner, Kinect, RGB-D image, Delaunay Triangulation.
Related
Ontology
Subjects/Areas/Topics:
Image Processing
;
Informatics in Control, Automation and Robotics
;
Robotics and Automation
;
Vision, Recognition and Reconstruction
Abstract:
In this paper, we present a new method for range data fusion from two heterogeneous range scanners for
accurate surface modeling of rough and highly unstructured terrain. First, we present the segmentation of
RGB-D images using the new framework of the GMM by employing the convex relaxation technique. After
segmentation of RGB-D images, we transform both the range data to a common reference frame using PCA
algorithm and apply the ICP algorithm to align both data in the reference frame. Based on a threshold criterion,
we fuse the range data in such a way that the coarser regions are obtained from Kinect sensor and finer regions
of plane are obtained from the Laser range sensor. After fusion, we apply Delaunay triangulation algorithm to
generate the highly accurate surface model of the terrain. Finally, the experimental results show the robustness
of the proposed approach.