Paper 13111-59
Machine vision with binocular meta-lens (Invited Paper)
22 August 2024 • 11:20 AM - 11:45 AM PDT | Conv. Ctr. Room 4
Abstract
Meta-lenses are advanced flat optical devices composed of artificial nanoantenna arrays. It manipulates the wavefront of light with the advantages of ultrathin, compact, and no spherical aberration. We have developed a series of intelligent machine vision systems with binocular meta-lens for the novel applications of particle image velocimetry (PIV), underwater stereo vision, edge-enhanced depth perception for ill-posed regions, and assisted driving vision. Meta-lens PIV demonstrates a new development trend for the PIV technique for rejuvenating traditional flow diagnostic tools toward a more compact, easy-to-deploy technique. A novel stereo-matching neural network, H-Net, was proposed to derive the disparity information, which incorporates the cross-pixel and cross-view interaction operations. The developed machine vision systems facilitated underwater imaging and assisted driving vision. With binocular meta-lens, multimodal perceptions are provided for machine vision systems in various novel applications.
Presenter
City Univ. of Hong Kong (Hong Kong, China)
Xiaoyuan Liu received her Ph.D degree from the Department of Electrical Engineering at the City University of Hong Kong in 2023. At present, she is a Postdoctoral Researcher with the State Key Laboratory of Terahertz and Millimeter Waves at the City University of Hong Kong. Her research interests focus on meta-lens and deep learning for the design and application of meta-devices.