Seungmin Leem
Papers
1
Total Citations
5
H-Index
1
About
Seungmin Leem is a researcher in computer vision and human-computer interaction, with a focus on gesture-based interfaces. His most-cited work, "A Robust Hand Gesture Recognition Using Combined Moment Invariants in Hand Shape" (2016, 5 citations), introduces a method for recognizing hand gestures by extracting moment features from hand shapes. Leem’s approach segments hand regions from video streams using skin color detection, offering a practical alternative to expensive depth-sensing devices like Kinect by relying on standard web cameras. This contribution advances accessible, real-time gesture recognition systems, with potential applications in sign language interpretation, virtual reality, and touchless control. While his citation count reflects a niche but growing field, Leem’s work demonstrates a commitment to robust, low-cost solutions for human-computer interaction, making gesture-based technology more inclusive and deployable in everyday environments. His research continues to inspire developments in feature extraction and pattern recognition for dynamic hand gestures.
Research Focus
Key Achievements
Top Papers
- 1