Prof. Dr. Didier Stricker
Dr. Alain Pagani
Dr. Gerd Reis
Eric Thil
Keonna Cunningham
Dr. Jason Raphael Rambach
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
Tewodros Amberbir Habtegebrial
Khurram Hashmi
Jigyasa Singh Katrolia
Andreas Kölsch
Onorina Kovalenko
Stephan Krauß
Paul Lesur
Muhammad Jameel Nawaz Malik
Michael Lorenz
Mina Ameli
Nareg Minaskan Karabid
Pramod Murthy
Mathias Musahl
Peter Neigel
Manthan Pancholi
María Alejandra Sánchez Marín
Dr. Kripasindhu Sarkar
Alexander Schäfer
René Schuster
Mohamed Selim
Dennis Stumpf
Yongzhi Su
Xiaoying Tan
Yaxu Xie
Murad Almadani
Ahmet Firintepe
Dr. Vladislav Golyanik
Dr. Aditya Tewari
André Luiz Brandão
Circular markers for camera pose estimation
Circular markers for camera pose estimation
Proceedings of the 12th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS 2011) International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS-2011), 12th, April 13-15, Delft, Netherlands
- Abstract:
- This paper presents a new system using circular markers to estimate the pose of a camera. Contrary to most markers-based systems using square markers, we advocate the use of circular markers, as we believe that they are easier to detect and provide a pose estimate that is more robust to noise. Unlike existing systems using circular markers, our method computes the exact pose from one single circular marker, and do not need specific points being explicitly shown on the marker (like center, or axes orientation). Indeed, the center and orientation is encoded directly in the marker's code. We can thus use the entire marker surface for the code design. After solving the back projection problem for one conic correspondence, we end up with two possible poses. We show how to find the marker's code, rotation and final pose in one single step, by using a pyramidal cross-correlation optimizer. The marker tracker runs at 100 frames/second on a desktop PC and 30 frames/second on a hand-held UMPC.