Kyoungwon Min
Papers
1
Total Citations
1
H-Index
1
About
Kyoungwon Min is a researcher specializing in embedded systems, real-time computer vision, and human-computer interaction, with a particular focus on efficient hand gesture recognition. His major contribution lies in addressing the computational bottleneck of accurate hand gesture recognition in resource-constrained environments. In his most cited work, "Design of hand skeleton extraction accelerator for a real-time hand gesture recognition" (2019), Min proposed a dedicated hardware accelerator that enables real-time hand skeleton extraction, overcoming the challenge of high computational demands that typically hinder embedded applications in automobiles, robotics, and gaming. This work demonstrates his expertise in bridging algorithmic complexity with practical hardware implementation, achieving real-time performance without sacrificing accuracy. While his citation count is currently modest, Min’s research is foundational for advancing intuitive, low-latency interfaces in autonomous systems and interactive devices. His work represents a critical step toward making sophisticated gesture recognition viable for everyday embedded platforms, highlighting his commitment to solving real-world latency and efficiency challenges in human-machine interaction.
Research Focus
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Top Papers
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