Title
Multi-Sensor Integration for Indoor 3D Reconstruction.
Abstract
Outdoor maps and navigation information delivered by modern services and technologies like Google Maps and Garmin navigators have revolutionized the lifestyle of many people. Motivated by the desire for similar navigation systems for indoor usage from consumers, advertisers, emergency rescuers/responders, etc., many indoor environments such as shopping malls, museums, casinos, airports, transit stations, offices, and schools need to be mapped. Typically, the environment is first reconstructed by capturing many point clouds from various stations and defining their spatial relationships. Currently, there is a lack of an accurate, rigorous, and speedy method for relating point clouds in indoor, urban, satellite-denied environments. This thesis presents a novel and automatic way for fusing calibrated point clouds obtained using a terrestrial laser scanner and the Microsoft Kinect by integrating them with a low-cost inertial measurement unit. The developed system, titled the Scannect, is the first joint static-kinematic indoor 3D mapper.
Year
DOI
Venue
2018
10.13140/RG.2.2.10534.42566
arXiv: Computer Vision and Pattern Recognition
Field
DocType
Volume
Geography of robotics,Laser scanning,Computer science,Future of robotics,Human–computer interaction,Artificial intelligence,Inertial measurement unit,Point cloud,Computer engineering,Machine learning,Robotics,3D reconstruction
Journal
abs/1802.07866
Citations 
PageRank 
References 
1
0.35
1
Authors
1
Name
Order
Citations
PageRank
Jacky C. K. Chow1293.83