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Colloquium Announcement on Nov. 26, 2018
W-Name Admin (IP: *.152.74.116) W-Date 2018-10-30 11:26 Hit 497

AI Sportscaster using Deep Learning and Ontology

Speaker: Prof. Yong-suk Choi (Dept. of Computer Science and Engineering, Hanyang University)

Date: Nov. 26, (Mon.), 2018

Time: 05:00 PM 

Location: Woo Jung Information & Communication bldg., Room 601

Hosted by Dept. of Brain & Cognitive Engineering, Korea University / Institute of Brain and Cognitive Engineering, Korea University / BK21+ Global Leader Development Division in Brain Engineering, Korea University / Interdisciplinary Major in Brain and Cognitive Science


There have been many studies to generate captions or explanations about images or videos using machine learning techniques. A combination of well-known CNN and RNN is often used to generate natural language captions from the features of image frames. Recently, many attention models are also used to understand more detailed and accurate visual contexts. Therefore, deep learning can be a good option to automatically make a caption on a variety of images and videos. However, when considering AI sportscaster like baseball-caster, AI has to create natural language narrations not only from shallow contextual information about who plays what, but also by deeper understanding and reasoning using player/team information, domain knowledge, and a variety of game statistics.

This talk first describes three vision models (scene classifier, player detection, motion recognition) to obtain contextual information from sport-video frames and then presents the usage of ontology to make sportscasting in baseball games. Our AI sportscaster also incorporates on-line text web data related to the target game into the ontology that is built in real-time. We finally illustrate our early version of AI sportscaster for a KBO baseball game by using game statistics and learning motion pictures from September 2017 to April 2018

File 최용석.pdf(118.8K)

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