Papers
8
Total Citations
40
H-Index
3
About
Vitaly Kober is a leading researcher in computer vision and robotics, specializing in 3D reconstruction, point cloud registration, and image restoration. His most impactful work, "Point Cloud Registration Based on Multiparameter Functional" (2021), has garnered 22 citations and addresses a critical challenge in autonomous driving and robotics: aligning 3D point clouds through rigid geometric transformations. Kober has also pioneered algorithms for reconstructing nonrigid objects using RGB-D depth cameras, with applications spanning medicine, agriculture, and virtual reality. His adaptive SLAM (Simultaneous Localization and Mapping) design (2019) enables robots to navigate unknown environments without GPS, while his work on 3D deformable object reconstruction (2019) achieves accurate real-time results using a single Kinect sensor. Beyond 3D vision, Kober has contributed to image restoration (2012), addressing degradation from motion or turbulence, and inpainting (2022) using nonlocal means filters. His latest research (2025) explores neural network-based point cloud registration with virtual points. With over 40 citations across his publications, Kober’s work bridges theoretical advances and practical applications, making him a key figure in enabling robust, real-time 3D perception for autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Point Cloud Registration Based on Multiparameter Functional22 citations · 2021
- 2
- 3Adaptive algorithm for the SLAM design with a RGB-D camera4 citations · 2019
- 4Reconstruction of 3D deformable objects using a single Kinect sensor3 citations · 2019
- 5
- 6Image Restoration Using Two-Dimensional Variations2 citations · 2012
- 7Impainting with a Nonlocal Means Filter2 citations · 2022
- 8