A Meta-Device for Intelligent Depth Perception
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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Detail(s)
Original language | English |
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Article number | 2107465 |
Journal / Publication | Advanced Materials |
Volume | 35 |
Issue number | 34 |
Online published | 20 Aug 2022 |
Publication status | Published - 24 Aug 2023 |
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DOI | DOI |
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Attachment(s) | Documents
Publisher's Copyright Statement
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85136887973&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(a25b0bd5-dd71-497a-93f9-2c8a8557b847).html |
Abstract
The optical illusion affects depth-sensing due to the limited and specific light-field information acquired by single-lens imaging. The incomplete depth information or visual deception would cause cognitive errors. To resolve this problem, an intelligent and compact depth-sensing meta-device that is miniaturized, integrated, and applicable for diverse scenes in all light levels is demonstrated. The compact and multifunction stereo vision system adopts an array with 3600 achromatic meta-lenses and a size of 1.2 × 1.2 mm2 to measure the depth over a 30 cm range with deep-learning support. The meta-lens array can act as multiple imaging lenses to collect light field information. It can also work with a light source as an active optical device to project a structured light. The meta-lens array can serve as the core functional component of a light-field imaging system under bright conditions or a structured-light projection system in the dark. The depth information in both ways can be analyzed and extracted by the convolutional neural network. This work provides a new avenue for the applications such as autonomous driving, machine vision, human–computer interaction, augmented reality, biometric identification, etc. © 2022 Wiley-VCH GmbH.
Research Area(s)
- deep learning, depth perception, light field imaging, meta-lens, neural networks, structured light, LIDAR
Citation Format(s)
A Meta-Device for Intelligent Depth Perception. / Chen, Mu Ku; Liu, Xiaoyuan; Wu, Yongfeng et al.
In: Advanced Materials, Vol. 35, No. 34, 2107465, 24.08.2023.
In: Advanced Materials, Vol. 35, No. 34, 2107465, 24.08.2023.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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