Motion Capture Pipeline Design for Interactive Exhibition Space: focused on MIVA project
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This paper explores the application of AI motion capture technology in exhibition spaces, particularly for interactive exhibits. We conduct a review of various motion capture solutions and analyze their advantages and disadvantages when applied to interactive exhibition spaces. Our analysis demonstrates the necessity and applicability of video-based AI motion capture technology in such spaces. Furthermore, we investigate motion capture solutions through the MIVA project as a case study for such a non-standardized exhibition. Finally, we propose a pipeline for motion capture technology that can be effectively applied by identifying and solving problems that arise during installation and application of the capture program in interactive exhibition spaces.
Abstract
This paper explores the application of AI motion capture technology in exhibition spaces, particularly for interactive exhibits. We conduct a review of various motion capture solutions and analyze their advantages and disadvantages when applied to interactive exhibition spaces. Our analysis demonstrates the necessity and applicability of video-based AI motion capture technology in such spaces. Furthermore, we investigate motion capture solutions through the MIVA project as a case study for such a non-standardized exhibition. Finally, we propose a pipeline for motion capture technology that can be effectively applied by identifying and solving problems that arise during installation and application of the capture program in interactive exhibition spaces.
참고문헌 (11)
- Gong, S. J., "Motion capture and video motion analysis", Sports Sci, 146, pp.40~45 (2019)
- Hordyj, Jacek, "Inverse Kinematics of anthropomorphic structures for vision systems applications" (2015)[DOI]
- Fernández-Baena, A., "Biomechanical Validation of Upper-Body and Lower-Body Joint Movements of Kinect Motion Capture Data for Rehabilitation Treatments", 2012 Fourth International Conference on Intelligent Networking and Collaborative Systems, pp.656~661 (2012)
- Pfister, A., "Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analysis", Journal of medical engineering &technology, 38(5), pp.274~280 (2014)
- Xie, K., "Physics-based human motion estimation and synthesis from videos", Proceedings of the IEEE, 2021, 11532~11541
- Jo Byeong-cheol, "Analysis of the success factors of the Avatar 3D movie and the possibility of Korean 3D content", Journal of Korean Contents Society, 10(9), pp.137~145 (2010)
- Vilchis, C., "Driving the future faces:Benchmarking state-of-the-art facial tracking technology for Digital Humans", ~ (2022)
- Ernest Edmonds, "The art of interaction", Digital Creativity, 21(4), pp.257~264 (2010)
- 김현주, "인터랙티브 미디어아트의 관객 경험 분석을 위한 융복합적 연구", 한국영상학회논문집, 17(3), pp.129~149 (2019), 한국영상학회[DOI]
- 김해윤, "3D 캐릭터의 얼굴 표정 애니메이션 마커리스 표정 인식 기술 비교 분석 -페이스웨어와 페이스쉬프트 방식 중심으로-", 만화애니메이션연구, (37), pp.221~245 (2014), 한국만화애니메이션학회[DOI]