Margrit Gelautz
Papers
8
Total Citations
88
H-Index
5
About
Margrit Gelautz is a leading researcher at the intersection of computer vision, human-robot interaction, and affective computing. Her work spans two compelling domains: enabling machines to see the world through event-based vision, and teaching robots to understand and mirror human social cues. In her foundational work on dynamic vision sensors, she developed improved cooperative stereo matching algorithms that leverage bio-inspired sensors for high-speed, low-power applications in surveillance and autonomous navigation. Simultaneously, Gelautz has made significant contributions to social robotics, investigating how body language, movement mirroring, and synchrony can enhance human-robot interaction. Her 2020 study on body language in affective human-robot interaction, along with her 2024 comprehensive review on movement mirroring, have each garnered substantial attention, with her most cited papers accumulating over 85 citations. She has also pioneered novel approaches to camera pose estimation using human head detection and developed kinematic models for humanoid imitation systems. Gelautz’s work on exaggerated nonverbal cues and the Pepper robot demonstrates her commitment to designing socially intelligent machines that can engage naturally with humans.
Research Focus
Key Achievements
Top Papers
- 1
- 2Body Language in Affective Human-Robot Interaction29 citations · 2020
- 3Advances in Embedded Computer Vision13 citations · 2014
- 4Body Movement Mirroring and Synchrony in Human–Robot Interaction6 citations · 2024
- 5Evaluation of Camera Pose Estimation Using Human Head Pose Estimation5 citations · 2023
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