Kwang In Kim is a senior lecturer of computer science at the University of Bath. He received a BSc in computer engineering from the Dongseo University in 1996, and MSc and PhD in computer engineering from the Kyungpook National University in 1998 and 2000, respectively. He was a post-doctoral researcher at KAIST, at the Max-Planck-Institute for Biological Cybernetics, at Saarland University, and at the Max-Planck-Institute for Informatics, from 2000 to 2013. Before joining Bath, he was a lecturer at the School of Computing and Communications, Lancaster University. His research interests include machine learning, vision, graphics, and human-computer interaction. His talk takes place in Wednesday, May 10th, 2017, at 3:30pm in room E105.

Toward Intuitive Imagery: User Friendly Manipulation and Exploration of Images and Videos

With the ubiquity of image and video capture devices, it is easy to form collections of images and video. Two important questions in this context are 1) how to retain the quality of individual images and videos and 2) how to explore the resulting large collections. Unlike professionally captured photographs and videos, the quality of the imageries that are casually captured by regular users are usually low. In this talk, we will discuss manipulating and improving such images and videos in several aspects. The central theme of the talk is user-friendliness. Unlike existing sophisticated algorithms, our approaches focus on enabling non-expert users freely manipulate and improve personal imagery collections. We present two specific examples in this context: image enhancement and video object removal. Existing interfaces to these video collections are often simply lists of text-ranked videos which do not exploit the visual content relationships between videos, or other implicit relationships such as spatial or geographical relationships. In the second part of the talk, we discuss data structures and interfaces that exploit content relationships present in images and videos.