Extraction robuste de primitives géométriques 3D dans un nuage de points et alignement basé sur les primitives

Dans ce projet, nous étudions les problèmes de rétro-ingénierie et de contrôle de la qualité qui jouent un rôle important dans la fabrication industrielle. La rétro-ingénierie tente de reconstruire un modèle 3D à partir de nuages de points, qui s’apparente au problème de la reconstruction de la surface 3D. Le contrôle de la qualité est un processus dans lequel la qualité de tous les facteurs impliqués dans la production est abordée. En fait, les systèmes ci-dessus nécessitent beaucoup d’intervention de la part d’un utilisateur expérimenté, résultat souhaité est encore loin soit une automatisation complète du processus. Par conséquent, de nombreux défis doivent encore être abordés pour atteindre ce résultat hautement souhaitable en production automatisée. La première question abordée dans la thèse consiste à extraire les primitives géométriques 3D à partir de nuages de points. Un cadre complet pour extraire plusieurs types de primitives à partir de données 3D est proposé. En particulier, une nouvelle méthode de validation est proposée pour évaluer la qualité des primitives extraites. À la fin, toutes les primitives présentes dans le nuage de points sont extraites avec les points de données associés et leurs paramètres descriptifs. Ces résultats pourraient être utilisés dans diverses applications telles que la reconstruction de scènes on d’édifices, la géométrie constructive et etc. La seconde question traiée dans ce travail porte sur l’alignement de deux ensembles de données 3D à l’aide de primitives géométriques, qui sont considérées comme un nouveau descripteur robuste. L’idée d’utiliser les primitives pour l’alignement arrive à surmonter plusieurs défis rencontrés par les méthodes d’alignement existantes. Ce problème d’alignement est une étape essentielle dans la modélisation 3D, la mise en registre, la récupération de modèles. Enfin, nous proposons également une méthode automatique pour extraire les discontinutés à partir de données 3D d’objets manufacturés. En intégrant ces discontinutés au problème d’alignement, il est possible d’établir automatiquement les correspondances entre primitives en utilisant l’appariement de graphes relationnels avec attributs. Nous avons expérimenté tous les algorithmes proposés sur différents jeux de données synthétiques et réelles. Ces algorithmes ont non seulement réussi à accomplir leur tâches avec succès mais se sont aussi avérés supérieus aux méthodes proposées dans la literature. Les résultats présentés dans le thèse pourraient s’avérér utilises à plusieurs applications.In this research project, we address reverse engineering and quality control problems that play significant roles in industrial manufacturing. Reverse engineering attempts to rebuild a 3D model from the scanned data captured from a object, which is the problem similar to 3D surface reconstruction. Quality control is a process in which the quality of all factors involved in production is monitored and revised. In fact, the above systems currently require significant intervention from experienced users, and are thus still far from being fully automated. Therefore, many challenges still need to be addressed to achieve the desired performance for automated production. The first proposition of this thesis is to extract 3D geometric primitives from point clouds for reverse engineering and surface reconstruction. A complete framework to extract multiple types of primitives from 3D data is proposed. In particular, a novel validation method is also proposed to assess the quality of the extracted primitives. At the end, all primitives present in the point cloud are extracted with their associated data points and descriptive parameters. These results could be used in various applications such as scene and building reconstruction, constructive solid geometry, etc. The second proposition of the thesis is to align two 3D datasets using the extracted geometric primitives, which is introduced as a novel and robust descriptor. The idea of using primitives for alignment is addressed several challenges faced by existing registration methods. This alignment problem is an essential step in 3D modeling, registration and model retrieval. Finally, an automatic method to extract sharp features from 3D data of man-made objects is also proposed. By integrating the extracted sharp features into the alignment framework, it is possible implement automatic assignment of primitive correspondences using attribute relational graph matching. Each primitive is considered as a node of the graph and an attribute relational graph is created to provide a structural and relational description between primitives. We have experimented all the proposed algorithms on different synthetic and real scanned datasets. Our algorithms not only are successful in completing their tasks with good results but also outperform other methods. We believe that the contribution of them could be useful in many applications

Automated calibration of multi-sensor optical shape measurement system

A multi-sensor optical shape measurement system (SMS) based on the fringe projection method and temporal phase unwrapping has recently been commercialised as a result of its easy implementation, computer control using a spatial light modulator, and fast full-field measurement. The main advantage of a multi-sensor SMS is the ability to make measurements for 360° coverage without the requirement for mounting the measured component on translation and/or rotation stages. However, for greater acceptance in industry, issues relating to a user-friendly calibration of the multi-sensor SMS in an industrial environment for presentation of the measured data in a single coordinate system need to be addressed. The calibration of multi-sensor SMSs typically requires a calibration artefact, which consequently leads to significant user input for the processing of calibration data, in order to obtain the respective sensor's optimal imaging geometry parameters. The imaging geometry parameters provide a mapping from the acquired shape data to real world Cartesian coordinates. However, the process of obtaining optimal sensor imaging geometry parameters (which involves a nonlinear numerical optimization process known as bundle adjustment), requires labelling regions within each point cloud as belonging to known features of the calibration artefact. This thesis describes an automated calibration procedure which ensures that calibration data is processed through automated feature detection of the calibration artefact, artefact pose estimation, automated control point selection, and finally bundle adjustment itself. [Continues.

Visualisation of articular motion in orthopaedics

Shouder replacement surgery is difficult surgery, with a relatively large risk on limited post-operative range of motion for patients. Adaptations to the anatomy of joints by placing a prosthesis affects the articulation of the joint. In this thesis we present a software system that simulates and visualises these effects. By loading a CT-scan of the shoulder of a patient we can simulate the range of motion of the joint and visualize limitations as a result of rigid structures of the joint. Surgeons may set up an operation plan and see what the consequences of the operation will be for the range of motion of the patient. The thesis investigates aspects that are relevant for the system. We describe an algorithm to convert the scan data to bone models. In addition, a validation experiment is presented. A method for motion registration and visualisation of recorded kinematic data is presented. Finally, this thesis concerns the application of the system to different surgical problems, such as hip arthroplasty and shoulder fractures.Annafonds Biomet Nederland Clinical Graphics DePuy JTE Johnson & Johnson Dutch Arthritis Association Litos/ Motek Medical TornierUBL - phd migration 201