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학술대회 Monocular Depth Estimation for Mobile Device
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저자
이용식, 이승재, 고종국
발행일
202111
출처
International Conference on Consumer Electronics (ICCE) 2021 : Asia, pp.498-500
DOI
https://dx.doi.org/10.1109/ICCE-Asia53811.2021.9641950
협약과제
21HH5100, 객체추출 및 실-가상 정합 지원 모바일 AR 기술 개발, 고종국
초록
Depth estimation is an important work in inferring scene geometry from 2D images applied in robotics, AR, autonomous driving, etc. Especially, monocular depth estimation is required for wide application in mobile devices. In this paper, a lightweight monocular depth estimation method is proposed for mobile devices and applied to mobile devices by changing the loss function and using network slimming. The result shows that our model requires low memory and reduces computational complexity that is suitable for mobile devices. The mobile device that we deploy is iPhone 11 Pro and it operates at over 30fps.
키워드
Monocular depth estimation, Network slimming
KSP 제안 키워드
Computational complexity, Estimation method, Mobile devices, Monocular depth estimation, autonomous driving, loss function