Selection of large-scale 3D point cloud data using gesture recognition

Abstract

An essential task when visualizing and analyzing large-scale 3D point cloud data is the selection of subsets of that data. This presents two challenges, the need for a selection method that is independent of the size of the dataset and how to interact with a 3D space effectively in a digital world still rooted in 2D interaction and visualization. We present an interface for defining volumes to select 3D point cloud data that uses hand gesture control with a Leap Motion device. The use of volumes is scalable to very large datasets, and the use of the Leap Motion gives the user access to the third dimension, facilitating interaction with the point cloud data. We illustrate with a large astronomical data archive hosted on the cloud that is retrieved on as-needed basis.