Dynamic Rendering of Remote Indoor Environments Using Real-Time Point Cloud Data

[+] Author and Article Information
Kevin Lesniak

Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA 16802

Conrad Tucker

Engineering Design, Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA 16802

1Corresponding author.

ASME doi:10.1115/1.4039472 History: Received October 15, 2017; Revised February 25, 2018


Modern RGB-D sensing systems are capable of reconstructing convincing virtual representations of real world environments. These virtual reconstructions can be used as the foundation for Virtual Reality (VR) and Augmented Reality (AR) environments due to their high quality visualizations. However, a main limitation of modern virtual reconstruction methods is the time it takes to incorporate new data and update the virtual reconstruction. This delay prevents the reconstruction from accurately rendering dynamic objects or portions of the environment (like an engineer performing an inspection of a machinery or lab space). The authors propose a multi-sensor method to dynamically capture objects in an indoor environment. The method automatically aligns the sensors using modern image homography techniques, and leverages Graphics Processing Units (GPUs) to process the large number of independent RGB-D data points and render them in real-time. Incorporating and aligning multiple sensors allows a larger area to be captured from multiple angles, providing a more complete virtual representation of the physical space. Performing processing on GPU's leverages the large number of processing cores available to minimize the delay between data capture and rendering. A case study using commodity RGB-D sensors, computing hardware, and standard TCP internet connections is presented to demonstrate the viability of the proposed method.

Copyright (c) 2018 by ASME
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