Prof. Dr. Didier Stricker
Dr. Alain Pagani
Dr. Gerd Reis
M.A. Eric Thil
Nicole Stephanie Buhlinger
Keonna Cunningham
Dr. Oliver Wasenmüller
Dr. Gabriele Bleser
Dr. Bertram Taetz
Sk Aziz Ali
Rashed Al Koutayni
Yuriy Anisimov
Jilliam Maria Diaz Barros
Ramy Battrawy
Hammad Butt
Mahdi Chamseddine
Steve Dias da Cruz
Fangwen Shu
Torben Fetzer
Michael Fürst
Christiano Couto Gava
Vladislav Golyanik
Tewodros Amberbir Habtegebrial
Hartmut Feld
Jigyasa Katrolia
Andreas Kölsch
Onorina Kovalenko
Stephan Krauß
Paul Lesur
Muhammad Jameel Nawaz Malik
Mina Ameli
Nareg Minaskan Karabid
Pramod Murthy
Mathias Musahl
Peter Neigel
Manthan Pancholi
Jason Raphael Rambach
María Alejandra Sánchez Marín
Kripasindhu Sarkar
Alexander Schäfer
René Schuster
Mohamed Selim
Dennis Stumpf
Yongzhi Su
Xiaoying Tan
André Luiz Brandão
Ahmet Firintepe
Aditya Tewari
Reality models for efficient registration in Augmented Reality
Reality models for efficient registration in Augmented Reality
PhD Thesis
- Abstract:
- The fundamental challenge of vision-based Augmented Reality is to make virtual objects and the real world coincide in a seamless way. In order to solve this registration problem, at least one real object present in the scene has to be detected, recognized and used by a corresponding algorithm to compute the position and orientation of the camera. In this thesis, we take a closer look at the representations of reality that can be used in the context of Augmented Reality. We define a Reality Model as a set of compact information about an object of interest and an algorithm that uses this information for estimating the pose of the camera. We first review existing Augmented Reality systems from the standpoint of these models and propose a classification based on the requirements of the pose estimation. We then present our novel approaches for different types of reality models, with applications in marker-based and texture-based pose estimation, 3D reconstruction, object detection and learning-based methods for local pose estimation.