Hajar Hiyadi
Papers
1
Total Citations
4
H-Index
1
About
Hajar Hiyadi is a researcher whose work lies at the intersection of computer vision, human-robot interaction, and 3D gesture recognition. Her most cited paper, "A Depth-based Approach for 3D Dynamic Gesture Recognition" (2015), introduced a novel technique for interpreting human gestures using depth data from the Kinect sensor. By computing the angles of the upper body skeleton, Hiyadi’s method enables more intuitive and responsive human-robot communication, a critical step toward seamless collaboration between people and machines. With 4 citations, this work has laid a foundation for further advances in non-verbal interaction systems. Hiyadi’s contributions are particularly notable for their practical application in robotics, where accurate, real-time gesture recognition is essential. Her research continues to influence the development of intelligent systems that can understand and react to human motion, making technology more accessible and natural to use.
Research Focus
Key Achievements
Top Papers
- 1A Depth-based Approach for 3D Dynamic Gesture Recognition4 citations · 2015