A Meta-Device for Intelligent Depth Perception

Mu Ku Chen (Co-first Author), Xiaoyuan Liu (Co-first Author), Yongfeng Wu, Jingcheng Zhang, Jiaqi Yuan, Zhengnan Zhang, Din Ping Tsai*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

104 Citations (Scopus)
273 Downloads (CityUHK Scholars)

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.
Original languageEnglish
Article number2107465
JournalAdvanced Materials
Volume35
Issue number34
Online published20 Aug 2022
DOIs
Publication statusPublished - 24 Aug 2023

Funding

We acknowledge the support from the University Grants Committee / Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. AoE/P-502/20 and GRF Project: 15303521), the Shenzhen Science and Technology Innovation Commission Grant (No. SGDX2019081623281169), the Department of Science and Technology of Guangdong Province (2020B1515120073), and City Univerity of Hong Kong (Project No. 9380131).

Research Keywords

  • deep learning
  • depth perception
  • light field imaging
  • meta-lens
  • neural networks
  • structured light
  • LIDAR

Publisher's Copyright Statement

  • COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: This is the peer reviewed version of the following article: Chen, M. K., Liu, X., Wu, Y., Zhang, J., Yuan, J., Zhang, Z., & Tsai, D. P. (2022). A Meta-Device for Intelligent Depth Perception. Advanced Materials, 35(34), [2107465], which has been published in final form at https://doi.org/10.1002/adma.202107465. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.

RGC Funding Information

  • RGC-funded

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