Michael Korn
Papers
1
Total Citations
5
H-Index
1
About
Michael Korn is a researcher in computer vision and robotics, with a primary focus on real-time 3D reconstruction and dynamic scene understanding. His most notable contribution is the development of KinFu MOT, an extension of the KinectFusion algorithm that enables simultaneous tracking of multiple moving objects alongside the static environment using a single depth camera. This work, published in 2015, addresses a critical limitation of traditional SLAM systems, which assume a static world. By allowing concurrent tracking and reconstruction of several moving objects, Korn's approach paves the way for more robust perception in dynamic, real-world settings—essential for applications in augmented reality, autonomous navigation, and human-robot interaction. While his citation count reflects a niche but growing field, the conceptual impact of his work is significant, bridging dense mapping with multi-object tracking. Korn's research continues to influence modern dynamic SLAM pipelines, demonstrating that real-time 3D reconstruction can extend beyond static environments to capture the complexity of motion.
Research Focus
Key Achievements
Top Papers
- 1KinFu MOT: KinectFusion with Moving Objects Tracking5 citations · 2015