Scribble based interactive 3D reconstruction via scene co-segmentation

In this paper, we present a novel interactive 3D reconstruction algorithm which renders a planar reconstruction of the scene. We consider a scenario where the user has taken a few images of a scene from multiple poses. The goal is to obtain a dense and visually pleasing reconstruction of the scene, including non-planar objects. Using simple user interactions in the form of scribbles indicating the surfaces in the scene, we develop an idea of 3D scribbles to propagate scene geometry across multiple views and perform co-segmentation of all the images into the different surfaces and non-planar objects in the scene. We show that this allows us to render a complete and pleasing reconstruction of the scene along with a volumetric rendering of the non-planar objects. We demonstrate the effectiveness of our algorithm on both outdoor and indoor scenes including the ability to handle featureless surfaces. Index Terms — image based modeling, interactive 3D re-construction 1

Interactive 3D Reconstruction: New Opportunities for Getting CAD-ready Models

A multitude of image-based 3D reconstruction and modeling techniques exist, which have achieved significant success in recent years. However, these techniques still lack certain abilities. For example, current 3D reconstruction techniques cannot decompose an object into its individual subparts. Thus, a printed model will consist of one single monolithic piece, which does not allow composing or decomposing parts, does not allow movable or flexible parts, and does not allow manufacturing the model from multiple different materials like wood, metal, or plastic. I reviewed the work in the research area of 3D reconstruction and provide an analysis of neglected research objectives and current drawbacks. Furthermore, I propose a mock-up of an interactive tool as a guideline for future research which describes a possible architecture, user interfaces, and processing pipeline, to overcome existing drawbacks of 3D reconstruction techniques

Interaktive Raumzeitrekonstruktion in der Computergraphik

High-quality dense spatial and/or temporal reconstructions and correspondence maps from camera images, be it optical flow, stereo or scene flow, are an essential prerequisite for a multitude of computer vision and graphics tasks, e.g. scene editing or view interpolation in visual media production. Due to the ill-posed nature of the estimation problem in typical setups (i.e. limited amount of cameras, limited frame rate), automated estimation approaches are prone to erroneous correspondences and subsequent quality degradation in many non-trivial cases such as occlusions, ambiguous movements, long displacements, or low texture. While improving estimation algorithms is one obvious possible direction, this thesis complementarily concerns itself with creating intuitive, high-level user interactions that lead to improved correspondence maps and scene reconstructions. Where visually convincing results are essential, rendering artifacts resulting from estimation errors are usually repaired by hand with image editing tools, which is time consuming and therefore costly. My new user interactions, which integrate human scene recognition capabilities to guide a semi-automatic correspondence or scene reconstruction algorithm, save considerable effort and enable faster and more efficient production of visually convincing rendered images.Raumzeit-Rekonstruktion in Form von dichten räumlichen und/oder zeitlichen Korrespondenzen zwischen Kamerabildern, sei es optischer Fluss, Stereo oder Szenenfluss, ist eine wesentliche Voraussetzung für eine Vielzahl von Aufgaben in der Computergraphik, zum Beispiel zum Editieren von Szenen oder Bildinterpolation. Da sowohl die Anzahl der Kameras als auch die Bildfrequenz begrenzt sind, ist das Rekonstruktionsproblem unterbestimmt, weswegen automatisierte Schätzungen häufig fehlerhafte Korrespondenzen für nichttriviale Fälle wie Verdeckungen, mehrdeutige oder große Bewegungen, oder einheitliche Texturen enthalten; jede Bildsynthese basierend auf den partiell falschen Schätzungen muß daher Qualitätseinbußen in Kauf nehmen. Man kann nun zum einen versuchen, die Schätzungsalgorithmen zu verbessern. Komplementär dazu kann man möglichst effiziente Interaktionsmöglichkeiten entwickeln, die die Qualität der Rekonstruktion drastisch verbessern. Dies ist das Ziel dieser Dissertation. Für visuell überzeugende Resultate müssen Bildsynthesefehler bislang manuell in einem aufwändigen Nachbearbeitungsschritt mit Hilfe von Bildbearbeitungswerkzeugen korrigiert werden. Meine neuen Benutzerinteraktionen, welche menschliches Szenenverständnis in halbautomatische Algorithmen integrieren, verringern den Nachbearbeitungsaufwand beträchtlich und ermöglichen so eine schnellere und effizientere Produktion qualitativ hochwertiger synthetisierter Bilder