Multi-Sensor Integration for Indoor 3D Reconstruction (2014)
Abstract / truncated to 115 words
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 ... toggle 1 keywordlidar rgb-d bundle adjustment with self-calibration slam icp microsoft kinect 3d cameras terrestrial laser scanners mems imu sensor fusion point cloud processing navigation mapping terrestrial laser scanners error modelling photogrammetry
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