Enhancing visibility for reliable underwater visual SLAM

Abstract

This talk consists of two parts. In the first part of this talk, various underwater image enhancement methods will be introduced. Visibility enhancement is very important in underwater imaging and vision-based robotics. We present three types of image enhancement, model-based, image processing based and deep learning-based approaches. In the second part of this talk, overcoming optical imaging limitation by using opti-acoustic factor will be introduced. Using sonar and optical images together is advantageous in many senses but with challenges. We will discuss the challenges and possible solutions when using the opti-acoustic sensor model.

Brief Biography

Ayoung Kim is the associate professor in the department of civil and environmental engineering with a joint affiliation at KI robotics and school of computing, Korea Advanced Institute of Science and Technology (KAIST). She received the B.S. and M.S. degrees in mechanical engineering from Seoul National University, Seoul, Korea, in 2005 and 2007, respectively, and the M.S. degree in electrical engineering and the Ph.D. degree in mechanical engineering from the University of Michigan (UM), Ann Arbor, in 2011 and 2012, respectively. She also worked as a post-doctoral researcher in naval architecture and marine engineering, UM in 2013 before she worked at Electronics and Telecommunications Research Institute (ETRI) as a senior researcher.

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