Sung Chun Lee

Title: Innovations of Sung Chun Lee in Object Tracking Technology

Introduction

Sung Chun Lee is an accomplished inventor based in Fairfax, VA (US). He has made significant contributions to the field of object tracking technology. His innovative approach focuses on enhancing the accuracy and efficiency of tracking objects in various applications.

Latest Patents

Sung Chun Lee holds a patent for a method titled "Feature selection for object tracking using motion mask, motion prediction, or both." This patent encompasses methods, systems, and apparatuses, including computer programs encoded on computer storage media, for feature selection in object tracking. The method involves obtaining first feature points of an object in a first image captured by a camera. It also includes obtaining a second image of the scene captured by the camera after the first image was taken. The process determines whether a motion prediction of the object is available, indicating where the object is likely located in the second image. If the motion prediction is available, the method identifies second feature points in the area of the second image that meet a similarity threshold with the first feature points. Finally, the object is detected in the second image using the identified second feature points.

Career Highlights

Sung Chun Lee's career is marked by his dedication to advancing technology in object tracking. His innovative methods have the potential to improve various applications, including surveillance, robotics, and augmented reality. With a focus on practical solutions, he continues to push the boundaries of what is possible in this field.

Collaborations

Sung Chun Lee has collaborated with notable colleagues, including Gang Qian and Sravanthi Bondugula. Their combined expertise has contributed to the development of advanced technologies in object tracking.

Conclusion

Sung Chun Lee's work in object tracking technology exemplifies the spirit of innovation and collaboration. His patent and contributions to the field highlight the importance of developing efficient methods for tracking objects in real-time applications.