Extracting structured models from raw scans of manufactured objects : a step towards embedded intelligent handheld 3D scanning
|Advisor:||Laurendeau, Denis; Gagné, Christian|
|Abstract:||The availability of fast and accurate 3D sensors has favored the development of different applications in assembly, inspection, Computer-Aided Design (CAD), reverse engineering, mechanical engineering, medicine, and entertainment, to list just a few. While 2D cameras capture 2D images of the surface of objects, either black-and-white or color, 3D cameras provide information on the geometry of an object surface. Today, newly introduced 3D cameras can acquire the appearance and geometry of objects concurrently. The popularity and availability of such these 3D models has opened new fields of interests, such as 3D model segmentation, 3D model recognition, estimation of 3D models’ parameters and even 3D modelling. In this project, we aim at recognizing different parts (primitives) of a 3D object, intelligently. For this purpose, we first prepare a database of 3D CAD primitives (i.g. planes, cylinders, cones, spheres and, tori). Then using segmentation algorithms, the complex objects are decomposed into their primitives and, by utilizing recognition techniques, a descriptor is extracted and associated to each primitive and, finally, a classifier is trained to learn the properties of primitives. The manuscript investigates different methods related to these challenges. An additional step is also proposed in this project which estimates the parameters of primitives and generate the CAD primitives that completes the whole process of reverse engineering.|
|Document Type:||Thèse de doctorat|
|Open Access Date:||23 April 2018|
|Collection:||Thèses et mémoires|
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