Minoo Hamissi
Papers
1
Total Citations
11
H-Index
1
About
Minoo Hamissi is a researcher whose work lies at the intersection of human-robot interaction and computer vision, with a particular focus on real-time gesture recognition. Her most cited paper, "Real-Time Hand Gesture Recognition Based on the Depth Map for Human Robot Interaction" (2013), introduces a novel method that leverages depth map data from Microsoft’s Kinect sensor to enable intuitive, non-verbal communication between humans and robots. By using depth information—which captures the distance of objects from a viewpoint—Hamissi’s approach allows for robust and efficient gesture recognition in real time, a critical requirement for practical robotic applications. This work has garnered 11 citations, reflecting its foundational role in advancing gesture-based interfaces. Hamissi’s contributions are notable for bridging the gap between affordable consumer hardware and sophisticated interaction systems, making gesture control more accessible. Her research has implications for assistive robotics, industrial automation, and immersive user interfaces, positioning her as a contributor to the growing field of natural human-machine communication.
Research Focus
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Top Papers
- 1