Past Research
Shape Detection of Mold Parts based on AI, 2019
- 작성자Artificial Intelligence Laboratory
- 조회수7
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OverviewDevelopment of a Specific Shape Recognition Algorithm in 2D Drawing of TV or Monitor Cover and Chassis Using Cascade R-CNNKey Researches- Object Detection- Object Orientation Estimation- Computer VisionProject ExplainationAs the replacement cycle of products is shortened due to various demands from consumers, the demand for mold manufacturing is increasing and the delivery period is getting shorter. The disadvantage of the mold design automation system developed to date is that it relies solely on the competence of the mold designer. Although CAD developers have released many shape analysis tools to reduce dependence on workers' capabilities, they cannot apply them to current businesses.Thus, in this study, cascade R-CNN was used to recognize certain features in TV covers and chassis 2D drawings. As a result of recognition, the shape part is displayed in the form of a boundary box, and the type of feature, the location from the center of the drawing, the degree of rotation (90 degree intervals), and the size of the boundary box by the width and width.Project DetailDonation: Samsung Electronics Global Technology CenterTerm :2019. 04. 01~ 2019. 12. 31.Expenses : 60,000,000 WONContact- Name: SeongHo Bak, Ph.D Course- E-mail: bakseongho@gm.gist.ac.kr
- 등록일2020-07-06 15:59:47
Developed intelligent UI/UX technology for AR glasses-based docent operation
- 작성자Artificial Intelligence Laboratory
- 조회수23
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OverviewDevelopment of UX optimized exhibition space for wearing augmented reality (AR)Space-based storytelling technology and emotional recognition (AI) technologyVirtual Character Docent Service TechnologyKey Researches- Recognition of gestures and developing viewer-centered gestures NUX- Developing chatbots and implementing information provision functions for audience conversation recognition- Development of a real-time wireless indoor visitors' information monitoring system based on UWB sensors- Development of a production tool for AR docents in museumsProject ExplainationIn this project, the exhibition space UX technology optimized for wearing augmented reality, space-based storytelling technology, and viewer sentiment recognition AI technology are designed to organize optimal information for individual visitors and to develop a service technology guided by virtual character docents through wearable augmented reality glass.We demonstrated optimized docent guidance service through wearable AR glass for visitors to the Shilla Hall of the National Museum of Korea.The artificial intelligence lab of Gwangju Institute of Science and Technology develops a real-time visiting behavior monitoring system by measuring the indoor location of the audience.The ultra-wideband (UWB) radar sensor is used to establish a wireless indoor positioning system and to develop a real-time viewer position, movement, and retention time monitoring system by relics.The goal is to develop AR docent service optimized for visitors by developing viewing characteristics analysis software by age, gender, etc.Based on real-time UWB measurement information in the future, we want to study customized service delivery technology that can actively provide appropriate services by analyzing characteristics of measured targets with AI.Publications- 이주순, 서호건, 이규빈. "초광대역 레이터를 이용한 관람 행테 분석 시스템". 스마트미디어저널. 2019, vol.8, no.4, pp. 85-90.- Joosoon Lee, Hogeon Seo, Kyoobin Lee. "Analysis of Museum Patrons' Behavior using Ultra-Wide Band Radar based Tracking System". The 8th International Conference on Smart MediaProject: Developed intelligent UI/UX technology for AR glasses-based docent operationDonation: Ministry of Culture, Sports and Tourism / Korea Creative Content AgencyTerm: 01/04/2017 ~ 31/12/2019 (33 months)Expense: 2,000,000,000\Consortium: Gwangju Institute of Science and Technology, Korean Culture Technology Institute, VIRNECT, Perpect-Storm, Sampartners, TILONContact- Name: Joosoon Lee, integrated Ph.D. program- Mail: joosoon1111@gist.ac.kr
- 등록일2020-06-25 10:31:36