6 papers · 1 filter
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…
On Representation of 3D Rotation in the Context of Deep Learning
Viktória Pravdová, Lukáš Gajdošech, Hassan Ali +1
This paper investigates various methods of representing 3D rotations and their impact on the learning process of deep neural networks. We evaluated the performance of ResNet18 netw…