Authors:
Panagiotis-Alexandros Bokaris
1
;
Damien Muselet
2
and
Alain Trémeau
2
Affiliations:
1
University of Paris-Saclay and Univ. Paris-Sud, France
;
2
Université Jean Monnet, France
Keyword(s):
3D Reconstruction, Cuboid Fitting, Kinect, RGB-D, RANSAC, Bounding Box, Point Cloud, Manhattan World.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Geometry and Modeling
;
Image-Based Modeling
;
Pattern Recognition
;
Software Engineering
Abstract:
The three-dimensional reconstruction of a scene is essential for the interpretation of an environment. In this
paper, a novel and robust method for the 3D reconstruction of an indoor scene using a single RGB-D image
is proposed. First, the layout of the scene is identified and then, a new approach for isolating the objects in
the scene is presented. Its fundamental idea is the segmentation of the whole image in planar surfaces and the
merging of the ones that belong to the same object. Finally, a cuboid is fitted to each segmented object by a
new RANSAC-based technique. The method is applied to various scenes and is able to provide a meaningful
interpretation of these scenes even in cases with strong clutter and occlusion. In addition, a new ground truth
dataset, on which the proposed method is further tested, was created. The results imply that the present work
outperforms recent state-of-the-art approaches not only in accuracy but also in robustness and time complexity.