Metasurface-Based Structured Light Sensing Without Triangulation

Chengzhi Li, Xin Li*, Cong He, Guangzhou Geng, Junjie Li, Xiaoli Jing*, Yongtian Wang, Lingling Huang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Structured light (SL) sensing technology, based on the triangulation principle, is widely employed for depth perception in various applications such as face recognition, human-computer interaction, machine vision, and more. In this approach, the baseline length, which refers to the distance between the projection device and the camera, is a critical parameter that affects depth measurement and system miniaturization. Recently, metasurfaces have emerged as promising devices for constructing compact optoelectronic systems due to their excellent performance in wavefront modulation of light and ultra-thin characteristics. In this study, a metasurface-based monocular SL depth detection scheme is proposed that incorporates a specially designed 3D holographic projection. Under this projected light field, the entire 3D space is labeled, and depth information can be obtained without considering the baseline length, which can further reduce the volume of SL systems. Additionally, a template-matching algorithm based on correlation coefficient analysis is developed and experimentally demonstrates its feasibility by precisely positioning objects. It is believed that this work opens up a new perspective for compact, lightweight, and flexible design of SL sensing systems, and has a promising future in quantitative detection, automatic location, and industrial measurement.

Original languageEnglish
Article number2302126
JournalAdvanced Optical Materials
Volume12
Issue number7
DOIs
Publication statusPublished - 5 Mar 2024

Keywords

  • 3D sensing
  • metasurface
  • multiplane holography
  • structured light

Fingerprint

Dive into the research topics of 'Metasurface-Based Structured Light Sensing Without Triangulation'. Together they form a unique fingerprint.

Cite this