Dr. Muhammad Zeshan Afzal

Prof. Dr. Didier Stricker

Dr. Alain Pagani

Keonna Cunningham

Dr. Oliver Wasenmüller

Dr. Gabriele Bleser

Dr. Bruno Mirbach

Dr. Jason Raphael Rambach

Dr. Bertram Taetz

Mhd Rashed Al Koutayni

Jilliam Maria Diaz Barros

Iuliia Brishtel

Mahdi Chamseddine

Steve Dias da Cruz

Ahmet Firintepe

Sophie Folawiyo

David Michael Fürst

Kamalveerkaur Garewal

Christiano Couto Gava

Leif Eric Goebel

Tewodros Amberbir Habtegebrial

Jigyasa Singh Katrolia

Andreas Kölsch

Onorina Kovalenko

Muhammad Jameel Nawaz Malik

Nareg Minaskan Karabid

Mohammad Minouei

Manthan Pancholi

Engr. Kumail Raza

Dr. Nadia Robertini

María Alejandra Sánchez Marín

Dr. Kripasindhu Sarkar

Alexander Schäfer

Pascal Schneider

Lukas Stefan Staecker

Dr. Vladislav Golyanik

Dr. Aditya Tewari

André Luiz Brandão

Accurate and Robust Spherical Camera Pose Estimation using Consistent Points

Accurate and Robust Spherical Camera Pose Estimation using Consistent Points
Christiano Couto Gava, Bernd Krolla, Didier Stricker
International Conference on Machine Vision (ICMV-07), November 19-21, Milan, Italy

Abstract:: This paper addresses the problem of multi-view camera pose estimation of high resolution, full spherical images. A novel approach to simultaneously retrieve camera poses along with a sparse point cloud is designed for large scale scenes. We introduce the concept of consistent points that allows to dynamically select the most reliable 3D points for nonlinear pose refinement. In contrast to classical bundle adjustment approaches, we propose to reduce the parameter search space while jointly optimizing camera poses and scene geometry. Our method notably improves accuracy and robustness of camera pose estimation, as shown by experiments carried out on real image data.

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