Edgar Seemann
Papers
2
Total Citations
179
H-Index
2
About
Edgar Seemann is a pioneer in the field of human-robot interaction (HRI), with a research focus on computer vision, gesture recognition, and 3D tracking. His most influential work centers on enabling robots to perceive and interpret human non-verbal cues in natural, unconstrained environments. In his seminal 2004 paper, "Head pose estimation using stereo vision for human-robot interaction" (134 citations), Seemann introduced a robust method for estimating head orientation from a distance, leveraging stereo depth data to overcome the limitations of single-camera systems. This foundational contribution allowed robots to infer a person’s attention and intent without requiring them to be stationary or close to the sensor. He further advanced the field with his work on "3D-tracking of head and hands for pointing gesture recognition" (45 citations), where he integrated color and disparity information into a multi-hypothesis tracking framework. This system enabled real-time, 3D localization of body parts, making pointing gestures a viable and intuitive command interface for robots. Seemann’s research has been instrumental in moving HRI from controlled lab settings to dynamic, real-world scenarios, and his citation record reflects the lasting impact of his vision-driven interaction paradigms.
Research Focus
Key Achievements
Top Papers
- 1Head pose estimation using stereo vision for human-robot interaction134 citations · 2004
- 2