18 citations · 56 across the 25 of their papers we have counts for
33 papers
Privacy-Preserving Structureless Visual Localization via Image Obfuscation
Vojtech Panek, Patrik Beliansky, Zuzana Kukelova +1
Visual localization is the task of estimating the camera pose of an image relative to a scene representation. In practice, visual localization systems are often cloud-based. Natura…
Are Minimal Radial Distortion Solvers Necessary for Relative Pose Estimation?
Charalambos Tzamos, Viktor Kocur, Yaqing Ding +2
Estimating the relative pose between two cameras is a fundamental step in many applications such as Structure-from-Motion. The common approach to relative pose estimation is to app…
Combining Absolute and Semi-Generalized Relative Poses for Visual Localization
Vojtech Panek, Torsten Sattler, Zuzana Kukelova
Visual localization is the problem of estimating the camera pose of a given query image within a known scene. Most state-of-the-art localization approaches follow the structure-bas…
Obfuscation Based Privacy Preserving Representations are Recoverable Using Neighborhood Information
Kunal Chelani, Assia Benbihi, Fredrik Kahl +2
Rapid growth in the popularity of AR/VR/MR applications and cloud-based visual localization systems has given rise to an increased focus on the privacy of user content in the local…
WildGaussians: 3D Gaussian Splatting in the Wild
Jonas Kulhanek, Songyou Peng, Zuzana Kukelova +2
While the field of 3D scene reconstruction is dominated by NeRFs due to their photorealistic quality, 3D Gaussian Splatting (3DGS) has recently emerged, offering similar quality wi…
Robust Self-calibration of Focal Lengths from the Fundamental Matrix
Viktor Kocur, Daniel Kyselica, Zuzana Kukelova
The problem of self-calibration of two cameras from a given fundamental matrix is one of the basic problems in geometric computer vision. Under the assumption of known principal po…
Privacy-Preserving Representations are not Enough -- Recovering Scene Content from Camera Poses
Kunal Chelani, Torsten Sattler, Fredrik Kahl +1
Visual localization is the task of estimating the camera pose from which a given image was taken and is central to several 3D computer vision applications. With the rapid growth in…
Visual Localization using Imperfect 3D Models from the Internet
Vojtech Panek, Zuzana Kukelova, Torsten Sattler
Visual localization is a core component in many applications, including augmented reality (AR). Localization algorithms compute the camera pose of a query image w.r.t. a scene repr…
Practical solutions to the relative pose of three calibrated cameras
Charalambos Tzamos, Viktor Kocur, Yaqing Ding +4
We study the challenging problem of estimating the relative pose of three calibrated cameras from four point correspondences. We propose novel efficient solutions to this problem t…
Sparse resultant based minimal solvers in computer vision and their connection with the action matrix
Snehal Bhayani, Janne Heikkilä, Zuzana Kukelova
Many computer vision applications require robust and efficient estimation of camera geometry from a minimal number of input data measurements, i.e., solving minimal problems in a R…
Partially calibrated semi-generalized pose from hybrid point correspondences
Snehal Bhayani, Viktor Larsson, Torsten Sattler +2
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
Vojtech Panek, Zuzana Kukelova, Torsten Sattler
Visual localization, i.e., the problem of camera pose estimation, is a central component of applications such as autonomous robots and augmented reality systems. A dominant approac…
Relative Pose from SIFT Features
Daniel Barath, Zuzana Kukelova
This paper proposes the geometric relationship of epipolar geometry and orientation- and scale-covariant, e.g., SIFT, features. We derive a new linear constraint relating the unkno…
Calibrated and Partially Calibrated Semi-Generalized Homographies
Snehal Bhayani, Torsten Sattler, Daniel Barath +3
In this paper, we propose the first minimal solutions for estimating the semi-generalized homography given a perspective and a generalized camera. The proposed solvers use five 2D-…
Minimal Solutions for Panoramic Stitching Given Gravity Prior
Yaqing Ding, Daniel Barath, Zuzana Kukelova
When capturing panoramas, people tend to align their cameras with the vertical axis, i.e., the direction of gravity. Moreover, modern devices, such as smartphones and tablets, are…
Globally Optimal Relative Pose Estimation with Gravity Prior
Yaqing Ding, Daniel Barath, Jian Yang +2
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.…
Making Affine Correspondences Work in Camera Geometry Computation
Daniel Barath, Michal Polic, Wolfgang Förstner +3
Local features e.g. SIFT and its affine and learned variants provide region-to-region rather than point-to-point correspondences. This has recently been exploited to create new min…
Computing stable resultant-based minimal solvers by hiding a variable
Snehal Bhayani, Zuzana Kukelova, Janne Heikkilä
Many computer vision applications require robust and efficient estimation of camera geometry. The robust estimation is usually based on solving camera geometry problems from a mini…
Infrastructure-based Multi-Camera Calibration using Radial Projections
Yukai Lin, Viktor Larsson, Marcel Geppert +3
Multi-camera systems are an important sensor platform for intelligent systems such as self-driving cars. Pattern-based calibration techniques can be used to calibrate the intrinsic…
From two rolling shutters to one global shutter
Cenek Albl, Zuzana Kukelova, Viktor Larsson +2
Most consumer cameras are equipped with electronic rolling shutter, leading to image distortions when the camera moves during image capture. We explore a surprisingly simple camera…
Minimal Rolling Shutter Absolute Pose with Unknown Focal Length and Radial Distortion
Zuzana Kukelova, Cenek Albl, Akihiro Sugimoto +2
The internal geometry of most modern consumer cameras is not adequately described by the perspective projection. Almost all cameras exhibit some radial lens distortion and are equi…
A sparse resultant based method for efficient minimal solvers
Snehal Bhayani, Zuzana Kukelova, Janne Heikkilä
Many computer vision applications require robust and efficient estimation of camera geometry. The robust estimation is usually based on solving camera geometry problems from a mini…
Minimal Solvers for Rectifying from Radially-Distorted Conjugate Translations
James Pritts, Zuzana Kukelova, Viktor Larsson +2
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…
Minimal Solvers for Rectifying from Radially-Distorted Scales and Change of Scales
James Pritts, Zuzana Kukelova, Viktor Larsson +2
This paper introduces the first minimal solvers that jointly estimate lens distortion and affine rectification from the image of rigidly-transformed coplanar features. The solvers…