Daniel Franz Treffer
Papers
1
Total Citations
38
H-Index
1
About
Daniel Franz Treffer has established himself as a researcher in computer vision and human-computer interaction, with a particular focus on hand segmentation and hand-object interaction analysis. His most-cited work, "Hand segmentation for hand-object interaction from depth map" (2017, 38 citations), addresses a critical preprocessing challenge in augmented reality, medical applications, and human-robot interaction. Treffer's key contribution lies in developing robust depth-based segmentation methods that overcome the limitations of traditional color-based approaches, which often fail when objects share skin-like hues or when dealing with varying skin pigmentation. This work has proven foundational for enabling more reliable hand tracking in complex, real-world environments. By shifting the focus from color to depth information, Treffer's research has helped advance the practical deployment of interactive systems that require precise hand-object boundary detection. His contributions continue to inform developments in gesture recognition and immersive technologies, where accurate hand segmentation remains a persistent challenge.
Research Focus
Key Achievements
Top Papers
- 1Hand segmentation for hand-object interaction from depth map38 citations · 2017