Underwater vision and 6D pose estimation - Ayoung Kim
2020 Intelligent Sensing Summer School
Underwater vision and 6D pose estimation
Ayoung Kim, KAIST
To enable robust manipulation in underwater, several components are required covering from perception to manipulation. Unfortunately, underwater experience different light conditions than the terrestrial environment and RGB sensing is very limited. In this talk, I would like to introduce (1) underwater image dehazing for visibility improvement and (2) deep-learning-based pose estimation for object grasping. For dehazing, three aspects including model-based, image-processing based, and learning-based approaches will be introduced. We will discuss the pros and cons of each approach. The second topic of 6D pose estimation exploits deep learning to learn underlying primitive for improved orientation estimation.
As part of the 2020 Intelligent Sensing Summer School: http://cis.eecs.qmul.ac.uk/school2020...