Josef Scharinger
Papers
8
Total Citations
163
H-Index
4
About
Josef Scharinger is a versatile researcher whose work spans robotics perception, brain-computer interfaces (BCIs), and human-machine interaction. His contributions have meaningfully advanced multiple fields at the intersection of computer vision, cognitive neuroscience, and intelligent systems. Scharinger's most influential work focuses on probabilistic frameworks for active perception and 3D scene modeling, with his 2010 paper on 6D object pose estimation garnering 70 citations — demonstrating the real-world value of his approach to handling uncertainty in cluttered, multi-object environments. Equally impactful is his research into motor imagery-based BCIs for stroke rehabilitation, a 2012 study with 66 citations that helped shift the BCI paradigm from mere substitution of lost function toward active neural rehabilitation. His more recent investigations explore RGB-D sensor calibration using Gaussian processes, monocular pose estimation for collaborative robotics, and bird's-eye-view human-machine interaction monitoring — collectively pointing to a sustained commitment to making intelligent systems safer and more perceptually capable in real-world industrial settings. Work on ECoG-based robot control through brain signals further highlights his interdisciplinary reach. Across his career, Scharinger has established himself as a thoughtful contributor bridging fundamental perception research with practical human-centered applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Motor Imagery Based Brain-Computer Interface for Stroke Rehabilitation66 citations · 2012
- 3
- 4
- 5Visual large-scale industrial interaction processing4 citations · 2019
- 6
- 73D Robot Pose Estimation from 2D Images4 citations · 2019
- 8