Paul Streli
Papers
1
Total Citations
4
H-Index
1
About
Paul Streli is a rising researcher at the forefront of egocentric vision and human-computer interaction, with a focused expertise in understanding how we physically engage with the world through touch. His primary research areas center on hand pose estimation, pressure sensing, and the development of novel datasets that bridge the gap between computer vision and tactile interaction. Streli’s most significant contribution to date is the creation of **EgoPressure**, a pioneering dataset that captures both hand pressure and pose from an egocentric perspective. This work, already garnering 4 citations since its 2025 release, directly addresses a critical bottleneck in the field: the lack of comprehensive, real-world data for training models that can interpret touch contact and applied force. By enabling more accurate estimation of these subtle interactions, Streli’s research has profound implications for advancing mixed reality interfaces, where understanding how a user grasps or manipulates a virtual object is key, and for robotics, where dexterous manipulation relies on tactile feedback. Through this foundational dataset, Streli is establishing a vital resource for the community, setting the stage for more intuitive and physically-aware interactive systems.
Research Focus
Key Achievements
Top Papers
- 1