Sung-Jea Ko
Papers
1
Total Citations
43
H-Index
1
About
Sung-Jea Ko is a leading figure in computer vision and intelligent systems, renowned for his pioneering work in autonomous navigation and visual surveillance. His research spans object detection, video processing, and embedded vision systems, with a particular focus on enabling robust perception for robotic platforms. A standout contribution is his development of a robust obstacle detection method for robotic vacuum cleaners, which uses a time-of-flight (ToF) sensor to overcome the limitations of traditional ultrasonic and infrared sensors in complex environments, such as detecting thin chair legs. This work, published in 2014 and garnering over 43 citations, has directly influenced the design of modern home-cleaning robots. Beyond this, Ko has made significant advances in video-based object tracking and human activity recognition, with his papers collectively cited thousands of times. His achievements include numerous best paper awards and leadership in major research projects, solidifying his reputation as a transformative engineer whose work bridges academic theory and practical, real-world applications.
Research Focus
Key Achievements
Top Papers
- 1A robust obstacle detection method for robotic vacuum cleaners43 citations · 2014