Seon-Min Rhee

Papers

Total Citations

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About

Seon-Min Rhee has made impactful contributions to intelligent robotics and computer vision, with a particular focus on 3D range image analysis and interest point detection. Her most-cited work, “SDTP: a robust method for interest point detection on 3D range images” (2014), introduces a novel detector that identifies salient structural points in 3D data, enabling more reliable object recognition and scene understanding. This method has garnered 6 citations, underscoring its relevance in the field. Rhee’s research addresses a fundamental challenge: selecting a few representative points from complex 3D scans to improve efficiency and accuracy in applications like robotic navigation and autonomous systems. Her work bridges the gap between theoretical computer vision and practical robotics, offering robust solutions for real-world environments. Beyond this paper, Rhee’s broader contributions advance the integration of 3D perception into intelligent systems, making her a notable figure in the development of more perceptive and autonomous machines. Her achievements highlight a dedication to solving core problems in visual computing, with lasting implications for both research and industry.