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Fast image-based localization using direct 2D-to-3D matching

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3 Author(s)
Sattler, T. ; RWTH Aachen Univ., Aachen, Germany ; Leibe, B. ; Kobbelt, L.

Recently developed Structure from Motion (SfM) reconstruction approaches enable the creation of large scale 3D models of urban scenes. These compact scene representations can then be used for accurate image-based localization, creating the need for localization approaches that are able to efficiently handle such large amounts of data. An important bottleneck is the computation of 2D-to-3D correspondences required for pose estimation. Current stateof- the-art approaches use indirect matching techniques to accelerate this search. In this paper we demonstrate that direct 2D-to-3D matching methods have a considerable potential for improving registration performance. We derive a direct matching framework based on visual vocabulary quantization and a prioritized correspondence search. Through extensive experiments, we show that our framework efficiently handles large datasets and outperforms current state-of-the-art methods.

Published in:

Computer Vision (ICCV), 2011 IEEE International Conference on

Date of Conference:

6-13 Nov. 2011