Dae-Hee Won
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Dae-Hee Won has a total of 17 co-authors. Here are the top co-authors by number of shared publications:
- Sangkyung Sung
Konkuk University
5 shared publications - Young Jae Lee
Department of Mechanical and Aerospace Engineering, Konkuk University, Seoul, South Korea
5 shared publications Jin-Soo Cho
2 shared publications- Dennis M. Akos
Aerospace Engineering Sciences, University of Colorado Boulder, Boulder, CO 80309, USA
1 shared publication Jeong-Ho Jo
1 shared publication- Jeongrae Kim
Department of Electrical and Electronic Engineering, Korea Aerospace University, Goyang 10540, Republic of Korea
1 shared publication
Latest Publications
- 27 January 2016
- Published by Springer Nature in GPS Solutions
- Vol. 21 (1) , 211-223
Snow depth estimation accuracy using a dual-interface GPS-IR model with experimental results
- 27 January 2016
- Published by Springer Nature in GPS Solutions
- Vol. 21 (1) , 211-223
Snow depth estimation accuracy using a dual-interface GPS-IR model with experimental results
- 29 November 2013
- Published by Springer Nature in International Journal of Control, Automation, and Systems
- Vol. 11 (6) , 1196-1203
Geometrical distortion integrated performance index for vision-based navigation system
- 29 November 2013
- Published by Springer Nature in International Journal of Control, Automation, and Systems
- Vol. 11 (6) , 1196-1203
Geometrical distortion integrated performance index for vision-based navigation system
- 1 January 2012
- Published by The Korean Society for Aeronautical & Space Sciences in Journal of the Korean Society for Aeronautical & Space Sciences
- Vol. 40 (1) , 35-42
Particle Filter Based Feature Points Tracking for Vision Based Navigation System
Particle Filter Based Feature Points Tracking for Vision Based Navigation System Feature Point Tracking;Particle Filter;KLT;Vision Based Navigation; In this study, a feature-points-tracking algorithm is suggested using a particle filter for vision based navigation system. By applying a dynamic model of the feature point, the tracking performance is increased in high dynamic condition, whereas a conventional KLT (Kanade-Lucas-Tomasi) cannot give a solution. Futhermore, the particle filter is introduced to cope with irregular characteristics of vision data. Post-processing of recorded vision data shows that the tracking performance of suggested algorithm is more robust than that of KLT in high dynamic condition.
- 1 January 2012
- Published by The Korean Society for Aeronautical & Space Sciences in Journal of the Korean Society for Aeronautical & Space Sciences
- Vol. 40 (1) , 35-42
Particle Filter Based Feature Points Tracking for Vision Based Navigation System
Particle Filter Based Feature Points Tracking for Vision Based Navigation System Feature Point Tracking;Particle Filter;KLT;Vision Based Navigation; In this study, a feature-points-tracking algorithm is suggested using a particle filter for vision based navigation system. By applying a dynamic model of the feature point, the tracking performance is increased in high dynamic condition, whereas a conventional KLT (Kanade-Lucas-Tomasi) cannot give a solution. Futhermore, the particle filter is introduced to cope with irregular characteristics of vision data. Post-processing of recorded vision data shows that the tracking performance of suggested algorithm is more robust than that of KLT in high dynamic condition.
- 1 March 2010
- Published by The Korean Society for Aeronautical & Space Sciences in Journal of the Korean Society for Aeronautical & Space Sciences
- Vol. 38 (3) , 236-242
Observability Analysis of a Vision-INS Integrated Navigation System Using Landmark
- 1 March 2010
- Published by The Korean Society for Aeronautical & Space Sciences in Journal of the Korean Society for Aeronautical & Space Sciences
- Vol. 38 (3) , 236-242
Observability Analysis of a Vision-INS Integrated Navigation System Using Landmark