Bernhard Zeisl, Torsten Sattler, Marc Pollefeys IEEE Int. Conf. on Computer Vision (ICCV) 2015 Image-based localization approaches aim to determine the camera pose from which an image was taken. Finding correct 2D-3D correspondences between query image features and 3D points in the scene model becomes harder as the size of the model increases. Current state-of-the-art
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Christian Haene, Torsten Sattler and Marc Pollefeys IROS, 2015 Mapping the environment is crucial to enable path planning and obstacle avoidance for self-driving vehicles and other robots. In this paper, we concentrate on ground-based vehicles and present an approach which extracts static obstacles from depth maps computed out of multiple consecutive images. In contrast to
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Gim Hee Lee, Marc Pollefeys, and Friedrich Fraundorfer 2014 IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) In this paper, we present our minimal 4-point and linear 8-point algorithms to estimate the relative pose of a multi-camera system with known vertical directions, i.e. known absolute roll and pitch angles. We solve the minimal
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Christian Haene, Nikolay Savinov, and Marc Pollefeys 2014 IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) Dense 3D reconstruction of real world objects containing textureless, reflective and specular parts is a challenging task. Using general smoothness priors such as surface area regularization can lead to defects in the form of disconnected parts or
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Gim Hee Lee, and Marc Pollefeys 2014 IEEE International Conference on Robotics and Automation (ICRA) A potential loop-closure image pair passes the geometric verification test if the number of inliers from the computation of the geometric constraint with RANSAC exceed a pre-defined threshold. The choice of the threshold is critical to the success of identifying
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Lionel Heng, Mathias Buerki, Gim Hee Lee, Paul Furgale, Roland Siegwart, and Marc Pollefeys 2014 IEEE International Conference on Robotics and Automation (ICRA) The online recalibration of multi-sensor systems is a fundamental problem that must be solved before complex automated systems are deployed in situations such as automated driving. In such situations, accurate knowledge of
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Gim Hee Lee, Bo Li, Marc Pollefeys, and Friedrich Fraundorfer International Symposium on Robotics Research (ISRR) 2013 In this paper, we propose a novel formulation to solve the pose estimation problem of a calibrated multi-camera system. The non-central rays that pass through the 3D world points and multi-camera system are elegantly represented as Pluecker lines.
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Our partners at the ETH Zurich Computer Vision and Geometry lab have released the calibration pipeline that we use in V-Charge. The code is open source and it should work for calibrating the intrinsics and extrinsics of any multi-camera system. View the overview webpage here: https://people.inf.ethz.ch/hengli/camodocal/ Get the code on github: https://github.com/hengli/camodocal
Bo Li, Lionel Heng, Kevin Koeser, and Marc Pollefeys 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems This paper presents a novel feature descriptorbased calibration pattern and a Matlab toolbox which uses the specially designed pattern to easily calibrate both the intrinsics and extrinsics of a multiple-camera system. In contrast to existing calibration patterns,
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Bo Li, Lionel Heng, Gim Hee Lee, and Marc Pollefeys 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems We propose an algorithm to estimate the relative camera pose using four feature correspondences and one relative rotation angle measurement. The algorithm can be used for relative pose estimation of a rigid body equipped with a
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