Fast and Robust Registration of multiple Depth-Sensors and Virtual Worlds

PubDate: November 2021

Teams: University of Bremen

Writers: Andre Mühlenbrock; Roland Fischer; René Weller; Gabriel Zachmann

PDF: Fast and Robust Registration of multiple Depth-Sensors and Virtual Worlds

Abstract

The precise registration between multiple depth sensors is a crucial prerequisite for many applications. Previous techniques frequently rely on RGB or IR images and checkerboard targets for feature detection. However, this prohibits the usage for use-cases where neither is available or where IR and depth images have different projections. Therefore, we present a novel registration approach that uses depth data exclusively for feature detection, making it more universally applicable while still achieving robust and precise results. We propose a combination of a custom 3D registration target — a lattice with regularly-spaced holes — and a feature detection algorithm that is able to reliably extract the lattice and its features from noisy depth images. In addition, we have integrated the registration procedure to a publicly available Unreal Engine 4 plugin that allows multiple point clouds captured by several depth cameras to be registered in a virtual environment. Despite the rather noisy depth images, we are able to quickly obtain a robust registration that yields an average deviation of 3.8 mm to 4.4 mm in our test scenarios.