Search Results for author:
Found 39 papers, 16 papers with code
Privacy-Preserving Representations are not Enough -- Recovering Scene Content from Camera Poses
In this paper, we show that an attacker can learn about details of a scene without any access by simply querying a localization service.
Visual Localization using Imperfect 3D Models from the Internet
An interesting, and underexplored, source of data for building scene representations are 3D models that are readily available on the Internet, e. g., hand-drawn CAD models, 3D models generated from building footprints, or from aerial images.
Relative pose of three calibrated and partially calibrated cameras from four points using virtual correspondences
Our solutions are based on the simple idea of generating one or two additional virtual point correspondences in two views by using the information from the locations of the four input correspondences in the three views.
Sparse resultant based minimal solvers in computer vision and their connection with the action matrix
Most state-of-the-art efficient polynomial solvers are based on the action matrix method that has been automated and highly optimized in recent years.
Privacy-Preserving Representations Are Not Enough: Recovering Scene Content From Camera Poses
In this paper, we show that an attacker can learn about details of a scene without any access by simply querying a localization service.
Partially calibrated semi-generalized pose from hybrid point correspondences
In this paper we study the problem of estimating the semi-generalized pose of a partially calibrated camera, i. e., the pose of a perspective camera with unknown focal length w. r. t.
MeshLoc: Mesh-Based Visual Localization
In this work, we thus explore a more flexible alternative based on dense 3D meshes that does not require features matching between database images to build the scene representation.
Relative Pose from SIFT Features
This paper proposes the geometric relationship of epipolar geometry and orientation- and scale-covariant, e. g., SIFT, features.
Relative Pose From a Calibrated and an Uncalibrated Smartphone Image
In this paper, we propose a new minimal and a non-minimal solver for estimating the relative camera pose together with the unknown focal length of the second camera.
Calibrated and Partially Calibrated Semi-Generalized Homographies
In this paper, we propose the first minimal solutions for estimating the semi-generalized homography given a perspective and a generalized camera.
Globally Optimal Relative Pose Estimation with Gravity Prior
Smartphones, tablets and camera systems used, e. g., in cars and UAVs, are typically equipped with IMUs (inertial measurement units) that can measure the gravity vector accurately.
Minimal Solutions for Panoramic Stitching Given Gravity Prior
When capturing panoramas, people tend to align their cameras with the vertical axis, i. e., the direction of gravity.
P1AC: Revisiting Absolute Pose From a Single Affine Correspondence
We introduce the first general solution to the problem of estimating the pose of a calibrated camera given a single observation of an oriented point and an affine correspondence.
Infrastructure-based Multi-Camera Calibration using Radial Projections
In particular, our approach is more robust than the naive approach of first estimating intrinsic parameters and pose per camera before refining the extrinsic parameters of the system.
Making Affine Correspondences Work in Camera Geometry Computation
The main advantage of such solvers is that their sample size is smaller, e. g., only two instead of four matches are required to estimate a homography.
Computing stable resultant-based minimal solvers by hiding a variable
The existing state-of-the-art methods for solving such systems are either based on Gr\"obner bases and the action matrix method, which have been extensively studied and optimized in the recent years or recently proposed approach based on a sparse resultant computation using an extra variable.
From two rolling shutters to one global shutter
Most consumer cameras are equipped with electronic rolling shutter, leading to image distortions when the camera moves during image capture.
Minimal Rolling Shutter Absolute Pose with Unknown Focal Length and Radial Distortion
The internal geometry of most modern consumer cameras is not adequately described by the perspective projection.
A sparse resultant based method for efficient minimal solvers
Our new method can be fully automatized and incorporated into existing tools for automatic generation of efficient polynomial solvers and as such it represents a competitive alternative to popular Gr\"obner basis methods for minimal problems in computer vision.
Minimal Solvers for Rectifying from Radially-Distorted Conjugate Translations
This paper introduces minimal solvers that jointly solve for radial lens undistortion and affine-rectification using local features extracted from the image of coplanar translated and reflected scene texture, which is common in man-made environments.
Minimal Solvers for Rectifying from Radially-Distorted Scales and Change of Scales
The proposed solvers use the affine invariant that coplanar repeats have the same scale in rectified space.
Homography from two orientation- and scale-covariant features
Two new general constraints are derived on the scales and rotations which can be used in any geometric model estimation tasks.
Radial Distortion Triangulation
It is iterative in nature, yet in practice, it converges in no more than five iterations.
Linear solution to the minimal absolute pose rolling shutter problem
Our best 6-point solver, based on the new alternation technique, shows an identical or even better performance than the state-of-the-art R6P solver and is two orders of magnitude faster.
A Benchmark of Selected Algorithmic Differentiation Tools on Some Problems in Computer Vision and Machine Learning
However, it is important for the success of algorithmic differentiation that such `simple' objective functions are handled efficiently, as so many problems in computer vision and machine learning are of this form.
Rectification from Radially-Distorted Scales
This paper introduces the first minimal solvers that jointly estimate lens distortion and affine rectification from repetitions of rigidly transformed coplanar local features.
Camera Pose Estimation With Unknown Principal Point
To estimate the 6-DoF extrinsic pose of a pinhole camera with partially unknown intrinsic parameters is a critical sub-problem in structure-from-motion and camera localization.
Beyond Grobner Bases: Basis Selection for Minimal Solvers
In this paper we show how we can make polynomial solvers based on the action matrix method faster, by careful selection of the monomial bases.
Beyond Gröbner Bases: Basis Selection for Minimal Solvers
In this paper we show how we can make polynomial solvers based on the action matrix method faster, by careful selection of the monomial bases.
Radially-Distorted Conjugate Translations
The solvers are derived from constraints induced by the conjugate translations of an imaged scene plane, which are integrated with the division model for radial lens distortion.
Making Minimal Solvers for Absolute Pose Estimation Compact and Robust
In this paper we present new techniques for constructing compact and robust minimal solvers for absolute pose estimation.
On the Two-View Geometry of Unsynchronized Cameras
We present new methods for simultaneously estimating camera geometry and time shift from video sequences from multiple unsynchronized cameras.
A clever elimination strategy for efficient minimal solvers
We present a new insight into the systematic generation of minimal solvers in computer vision, which leads to smaller and faster solvers.
Distortion Varieties
The distortion varieties of a given projective variety are parametrized by duplicating coordinates and multiplying them with monomials.
Rolling Shutter Absolute Pose Problem With Known Vertical Direction
We compare our R5Pup to the state of the art RS and perspective methods and demonstrate that it outperforms them when vertical direction is known in the range of accuracy available on modern mobile devices.
Efficient Intersection of Three Quadrics and Applications in Computer Vision
In this paper, we present a new algorithm for finding all intersections of three quadrics.
Efficient Solution to the Epipolar Geometry for Radially Distorted Cameras
In this paper, we present a new efficient solution to this problem that uses 10 image correspondences.
R6P - Rolling Shutter Absolute Camera Pose
Therefore we can use the standard P3P algorithm to estimate camera orientation and to bring the camera rotation matrix close to the identity.
Radial Distortion Homography
The importance of precise homography estimation is often underestimated even though it plays a crucial role in various vision applications such as plane or planarity detection, scene degeneracy tests, camera motion classification, image stitching, and many more.
