Semi-Automatic Range to Range Registration: A Feature-Based Method
3DIM '05 Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling
MMM-classification of 3D range data
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
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This work presents a novel approach to registering multiple range images on top of a Google Maps image. The fundamental concept behind the method is matching completely different types of input with each other using classification as a middleman. Range images and Google Maps images are separated into classes, and the range image is also projected into a 2D top-down template image. The template image can then be matched against the Google Maps image to find its location and orientation on the map, which can be used for registering the range images. An experiment comparing this technique against using GPS to find position and orientation showed that it is effective at automatically constructing a reasonable large-scale 3D model whereas GPS would be completely ineffective.