Authors:
Naja von Schmude
1
;
Pierre Lothe
2
and
Bernd Jähne
3
Affiliations:
1
Robert Bosch GmbH and Ruprecht-Karls-Universität Heidelberg, Germany
;
2
Robert Bosch GmbH, Germany
;
3
Ruprecht-Karls-Universität Heidelberg, Germany
Keyword(s):
Relative Pose Estimation, Lines, Clustering, Monocular Camera, Visual Odometry.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Optical Flow and Motion Analyses
;
Pattern Recognition
;
Robotics
;
Shape Representation and Matching
;
Software Engineering
Abstract:
This paper tackles the problem of relative pose estimation between two monocular camera images in textureless
scenes. Due to a lack of point matches, point-based approaches such as the 5-point algorithm often fail
when used in these scenarios. Therefore we investigate relative pose estimation from line observations. We
propose a new approach in which the relative pose estimation from lines is extended by a 3D line direction
estimation step. The estimated line directions serve to improve the robustness and the efficiency of all processing
phases: they enable us to guide the matching of line features and allow an efficient calculation of
the relative pose. First, we describe in detail the novel 3D line direction estimation from a single image by
clustering of parallel lines in the world. Secondly, we propose an innovative guided matching in which only
clusters of lines with corresponding 3D line directions are considered. Thirdly, we introduce the new relative
pose estimation based on
3D line directions. Finally, we combine all steps to a visual odometry system. We
evaluate the different steps on synthetic and real sequences and demonstrate that in the targeted scenarios we
outperform the state-of-the-art in both accuracy and computation time.
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