Abstract
Estimation of a camera pose (position and orientation) from an image, given a 3d model of the world, is a topic of great interest in many current fields of research. When aiming for a model based pose estimation approach, several questions arise: What is the model? How do we acquire a model? How is the image linked to the model? How is a pose computed and verified using the latter information? In this paper we present a new approach towards model based pose estimation based solely on SURF features. We give a formal definition of our model, show how to build such a model from image data automatically, how to integrate two partial models, and how pose estimation for new images works.
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Decker, P., Paulus, D. (2011). Model Based Pose Estimation Using SURF. In: Koch, R., Huang, F. (eds) Computer Vision – ACCV 2010 Workshops. ACCV 2010. Lecture Notes in Computer Science, vol 6469. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22819-3_2
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DOI: https://doi.org/10.1007/978-3-642-22819-3_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22818-6
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