Title
Visual Map Construction Using RGB-D Sensors for Image-Based Localization in Indoor Environments.
Abstract
RGB-D sensors capture RGB images and depth images simultaneously, which makes it possible to acquire the depth information at pixel level. This paper focuses on the use of RGB-D sensors to construct a visual map which is an extended dense 3D map containing essential elements for image-based localization, such as poses of the database camera, visual features, and 3D structures of the building. Taking advantage of matched visual features and corresponding depth values, a novel local optimization algorithm is proposed to achieve point cloud registration and database camera pose estimation. Next, graph-based optimization is used to obtain the global consistency of themap. On the basis of the visualmap, the image- based localizationmethod is investigated, making use of the epipolar constraint. The performance of the visual map construction and the image- based localization are evaluated on typical indoor scenes. The simulation results show that the average position errors of the database camera and the query camera can be limited to within 0.2 meters and 0.9 meters, respectively.
Year
DOI
Venue
2017
10.1155/2017/8037607
JOURNAL OF SENSORS
Field
DocType
Volume
Computer vision,Epipolar geometry,Image based,Pose,Pixel,Artificial intelligence,RGB color model,Local search (optimization),Engineering,Global consistency,Point cloud
Journal
2017
ISSN
Citations 
PageRank 
1687-725X
2
0.37
References 
Authors
14
3
Name
Order
Citations
PageRank
Guanyuan Feng130.75
Lin Ma2185.63
Xuezhi Tan38014.98