Sewon Lee

Papers

Total Citations

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About

Sewon Lee is a robotics researcher whose work centers on computer vision and autonomous navigation, with a particular focus on improving object tracking for mobile robots operating in indoor environments. Lee’s most cited contribution, "Modified Otsu's method for indoor mobile robot tracking system" (2014), addresses a critical bottleneck in vision-based tracking: the thresholding step in image pre-processing. By proposing a refined version of Otsu’s method, Lee demonstrated how an optimized global thresholding algorithm can significantly enhance both the accuracy and computational efficiency of object tracking—a fundamental challenge for real-time robotic systems. While the paper has garnered 3 citations, its value lies in its targeted improvement of a widely used technique, offering a practical solution for researchers working on indoor robot navigation and surveillance. Lee’s work underscores the importance of foundational image processing steps in enabling reliable autonomous behavior, and it serves as a useful reference for those seeking to balance performance and precision in tracking applications.