5 papers
Detecting 3D Line Segments for 6DoF Pose Estimation with Limited Data
Matej Mok, Lukáš Gajdošech, Michal Mesároš +2
The task of 6DoF object pose estimation is one of the fundamental problems of 3D vision with many practical applications such as industrial automation. Traditional deep learning ap…
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…
Gaze Estimation for Human-Robot Interaction: Analysis Using the NICO Platform
Matej Palider, Omar Eldardeer, Viktor Kocur
This paper evaluates the current gaze estimation methods within an HRI context of a shared workspace scenario. We introduce a new, annotated dataset collected with the NICO robotic…
Efficient Vision-based Vehicle Speed Estimation
Andrej Macko, Lukáš Gajdošech, Viktor Kocur
This paper presents a computationally efficient method for vehicle speed estimation from traffic camera footage. Building upon previous work that utilizes 3D bounding boxes derived…
RePoseD: Efficient Relative Pose Estimation With Known Depth Information
Yaqing Ding, Viktor Kocur, Václav Vávra +4
Recent advances in monocular depth estimation methods (MDE) and their improved accuracy open new possibilities for their applications. In this paper, we investigate how monocular d…