Deducing the Location of Glass Windows in 3D Indoor Environments

Over the years, the pace at which data is generated keeps on increasing. As a consequence, the data itself no longer holds the highest value, but rather the information and context the data captures are. This principle also holds in the 3D environment modelling scene, as accurately depicting an environment holds more value than the number of...

A comparative study of point clouds semantic segmentation using three different neural networks on the railway station dataset

Point cloud data have rich semantic representations and can benefit various applications towards a digital twin. However, they are unordered and anisotropically distributed, thus being unsuitable for a typical Convolutional Neural Networks (CNN) to handle. With the advance of deep learning, several neural networks claim to have solved the...

SCIPoC: Semantic Classification of Indoor Point Cloud: A study into the possibilities of classifying indoor point cloud using a Deep Learning approach

With the constantly evolving range of applications for technology the quality and amount of data constantly increases as well. In this growing data environment, there is a constant search to provide more value to all data that is available for as little effort as possible. Our research tries to add such additional value by diving into the...