Dilip K. Prasad
Nanyang Technological University, UiT The Arctic University of Norway
Papers
7
Total Citations
335
H-Index
7
About
Dilip K. Prasad is a leading researcher in computer vision and robotics, whose work bridges fundamental geometric algorithms with real-world robotic manipulation. His key research areas include ellipse fitting and detection, object pose estimation, and robotic grasping. Prasad’s major contribution is the development of “ElliFit” (2012, 165 citations), an unconstrained, non-iterative, least-squares method for geometric ellipse fitting that has become a foundational tool in the field. Building on this, he has pioneered fast ellipse detection techniques using gradient information, enabling real-time robotic manipulation of cylindrical objects in dynamic environments—such as cans, cups, and pipes—with applications in industrial and household automation. His work on object pose estimation via pruned Hough forests (2020, 35 citations) and efficient pose estimation from single RGB-D images (2018, 17 citations) has advanced robotic grasp in cluttered, partially occluded scenes. Notably, his research on grasp stability through contact stiffness (2019, 23 citations) provides a generalized quality evaluation, enhancing robotic dexterity. With over 300 total citations, Prasad’s impact is evident in his ability to translate geometric primitives into practical robotic solutions, making him a key figure in the intersection of computer vision and autonomous manipulation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7