Markerless Camera Pose Estimation – An Overview

Markerless Camera Pose Estimation – An Overview
Tobias Nöll, Alain Pagani, Didier Stricker
Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering International Research Training Group Workshop (IRTG-1131), March 19-21, Bodega Bay, CA, USA

Abstract:: As shown by the human perception, a correct interpretation of a 3D scene on the basis of a 2D image is possible without markers. Solely by identifying natural features of different objects, their locations and orientations on the image can be identified. This allows a three dimensional interpretation of a two dimensional pictured scene. The key aspect for this interpretation is the correct estimation of the camera pose, i.e. the knowledge of the orientation and location a picture was recorded. This paper is intended to provide an overview of the usual camera pose estimation pipeline as well as to present and discuss the several classes of pose estimation algorithms.

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Markerless Camera Pose Estimation – An Overview

Abstract:: As shown by the human perception, a correct interpretation of a 3D scene on the basis of a 2D image is possible without markers. Solely by identifying natural features of different objects, their locations and orientations on the image can be identified. This allows a three dimensional interpretation of a two dimensional pictured scene. The key aspect for this interpretation is the correct estimation of the camera pose, i.e. the knowledge of the orientation and location a picture was recorded. This paper is intended to provide an overview of the usual camera pose estimation pipeline as well as to present and discuss the several classes of pose estimation algorithms.

Back to the overview

Link 1