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학술대회 A Bayesian Sensor Fusion Scheme for Attitude Tracking
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저자
전준기, 김화숙, 정우석, 김선중
발행일
201702
출처
International Conference on Advanced Communication Technology (ICACT) 2017, pp.633-636
DOI
https://dx.doi.org/10.23919/ICACT.2017.7890168
협약과제
16MH1800, 몰입형 스크린 미디어 서비스산업 촉진을 위한 스마트스페이스 기술개발, 김선중
초록
Accurate attitude tracking is a vital process in AR/VR applications. To satisfy its stringent requirement, multiple types of sensors, such as IMU and vision sensors, must cooperate, as each type of sensors has its own set of advantages complementing each other. However, fusion of different types of sensors is not a trivial task. We have previously proposed an attitude tracking algorithm using an IMU, which belongs to the category of recursive Bayesian filtering. In this paper, we propose a both theoretically reasonable and practically useful sensor fusion scheme based on Bayesian statistics, to extend and complement our previous algorithm. Implementation of our scheme for an AR application is also successfully done.
키워드
AR (augmented reality), Attitude tracking, HMD (head mounted display), IMU (inertial measurement unit), VR (virtual reality)
KSP 제안 키워드
Attitude tracking, Augmented reality(AR), Bayesian Statistics, Head-mounted display(HMD), Inertial Measurement Unit(IMU), Recursive Bayesian filtering, Tracking algorithm, Virtual Reality(VR), Vision sensor, fusion scheme, sensor fusion