Title
Rapid 3D Modeling and Parts Recognition on Automotive Vehicles Using a Network of RGB-D Sensors for Robot Guidance
Abstract
This paper presents an approach for the automatic detection and fast 3D profiling of lateral body panels of vehicles. The work introduces a method to integrate raw streams from depth sensors in the task of 3D profiling and reconstruction and a methodology for the extrinsic calibration of a network of Kinect sensors. This sensing framework is intended for rapidly providing a robot with enough spatial information to interact with automobile panels using various tools. When a vehicle is positioned inside the defined scanning area, a collection of reference parts on the bodywork are automatically recognized from a mosaic of color images collected by a network of Kinect sensors distributed around the vehicle and a global frame of reference is set up. Sections of the depth information on one side of the vehicle are then collected, aligned, and merged into a global RGB-D model. Finally, a 3D triangular mesh modelling the body panels of the vehicle is automatically built. The approach has applications in the intelligent transportation industry, automated vehicle inspection, quality control, automatic car wash systems, automotive production lines, and scan alignment and interpretation.
Year
DOI
Venue
2013
10.1155/2013/832963
JOURNAL OF SENSORS
Field
DocType
Volume
Computer vision,Profiling (computer programming),RGB color model,Production line,Vehicle inspection,Artificial intelligence,Engineering,Intelligent transportation system,Robot,3D modeling,Automotive industry
Journal
2013
ISSN
Citations 
PageRank 
1687-725X
5
0.51
References 
Authors
14
4
Name
Order
Citations
PageRank
Alberto Chávez-Aragón1154.61
Rizwan Macknojia260.86
Pierre Payeur313327.35
Robert Laganière430035.20