Depth image super resolution method for time-of-flight camera based on machine learning

Yoon-Seop Lim; Sung-Hyun Lee; Wook-Hyeon Kwon; Yong-Hwa Park

doi:10.1117/12.2609507

2 March 2022 Depth image super resolution method for time-of-flight camera based on machine learning

Yoon-Seop Lim, Sung-Hyun Lee, Wook-Hyeon Kwon, Yong-Hwa Park

Proceedings Volume 12019, AI and Optical Data Sciences III; 120190S (2022) https://doi.org/10.1117/12.2609507
Event: SPIE OPTO, 2022, San Francisco, California, United States

Conference Poster

Abstract

Time-of-flight (ToF) measurement sensor is widely used to measure 3D depth. However, conventional ToF cameras has relatively low resolution compared to the RGB camera. To utilize such depth image of low resolution effectively in various research fields, low resolution depth image of ToF sensor should be increased. Meanwhile, ToF sensor also has problem related saturated pixels and missing pixels. A novel depth completion algorithm is proposed in this paper to improve the 3D depth image of ToF camera in terms of image resolution and abnormal pixels. Specifically, low resolution depth images and relatively high resolution RGB images are fused in machine learning architecture. The performance of this proposed depth completion algorithm is demonstrated under various experimental conditions.

Conference Presentation

Citation Download Citation

Yoon-Seop Lim, Sung-Hyun Lee, Wook-Hyeon Kwon, and Yong-Hwa Park "Depth image super resolution method for time-of-flight camera based on machine learning", Proc. SPIE 12019, AI and Optical Data Sciences III, 120190S (2 March 2022); https://doi.org/10.1117/12.2609507

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available