Search results for "Scene Reconstruction"
showing 3 items of 3 documents
Semantic-based Technique for the Automation the 3D Reconstruction Process
2010
Pages: 191 to 198, ISBN: 978-1-61208-104-5; International audience; The reconstruction of 3D objects based on point clouds data presents a major task in many application field since it consumes time and require human interactions to yield a promising result. Robust and quick methods for complete object extraction or identification are still an ongoing research topic and suffer from the complex structure of the data, which cannot be sufficiently modeled by purely numerical strategies. Our work aims at defining a new way of automatically and intelligently processing of 3D point clouds from a 3D laser scanner. This processing is based on the combination of 3D processing technologies and Semant…
3D Scene Reconstruction Using Kinect
2014
The issue of the automatic reconstruction of 3D scenes has been addressed in several chapters over the last few years. Many of them describe techniques for processing stereo vision or range images captured by high quality range sensors. However, due to the high price of such input devices, most of the methods proposed in the literature are not suitable for real-world scenarios. This chapter proposes a method designed to reconstruct 3D scenes perceived by means of a cheap device, namely the Kinect sensor. The scene is efficiently represented as a composition of superquadric shapes so as to obtain a compact description of environment, however complex it may be. The approach proposed here is i…
Knowledge Base Approach for 3D Objects Detection in Point Clouds Using 3D Processing and Specialists Knowledge
2012
This paper presents a knowledge-based detection of objects approach using the OWL ontology language, the Semantic Web Rule Language, and 3D processing built-ins aiming at combining geometrical analysis of 3D point clouds and specialist's knowledge. Here, we share our experience regarding the creation of 3D semantic facility model out of unorganized 3D point clouds. Thus, a knowledge-based detection approach of objects using the OWL ontology language is presented. This knowledge is used to define SWRL detection rules. In addition, the combination of 3D processing built-ins and topological Built-Ins in SWRL rules allows a more flexible and intelligent detection, and the annotation of objects …