Abstract
We present a novel 3D reconstruction system that can generate a stable triangle mesh using data from multiple RGB-D sensors in real time for dynamic scenes. The first part of the system uses moving least squares (MLS) point set surfaces to smooth and filter point clouds acquired from RGB-D sensors. The second part of the system generates triangle meshes from point clouds. The whole pipeline is executed on the GPU and is tailored to scale linearly with the size of the input data. Our contributions include changes to the MLS method for improving meshing, a fast triangle mesh generation method and GPU implementations of all parts of the pipeline.
Highlights
For most 3D reconstruction systems, the process can be divided conceptually into three stages: 1. Data acquisition Traditionally, acquiring a real-time 3D structure of an environment using stereo or multiview stereo algorithms has been a challenging and computationally expensive stage
We present a novel 3D reconstruction system that can generate a stable triangle mesh using data from multiple RGB-D sensors in real time for dynamic scenes
The first part of the system uses moving least squares (MLS) point set surfaces to smooth and filter point clouds acquired from RGB-D sensors
Summary
For most 3D reconstruction systems, the process can be divided conceptually into three stages: 1. Data acquisition Traditionally, acquiring a real-time 3D structure of an environment using stereo or multiview stereo algorithms has been a challenging and computationally expensive stage. For most 3D reconstruction systems, the process can be divided conceptually into three stages: 1. The advent of consumer RGB-D sensors has enabled the 3D reconstruction process to become truly real-time, but RGB-D devices still have their own drawbacks. The generated depth maps tend to be noisy, and the scene coverage is restricted due to the sensor’s limited focal length, making the following process stages more difficult to achieve. Some commonly used formats are point clouds, triangle meshes and depth maps. Our work involves both surface reconstruction and triangle mesh generation. J Real-Time Image Proc (2019) 16:2247–2259 extraction stage, since they are the most commonly used representation in computer graphics and are view independent
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
