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360° structured light with learned metasurfaces
DOI:10.1038/s41566-024-01450-x.png)
摘要
En 中文
Structured light has proven instrumental in three-dimensional imaging, LiDAR and holographic light projection. Metasurfaces, comprising subwavelength-sized nanostructures, facilitate 180 degrees-field-of-view structured light, circumventing the restricted field of view inherent in traditional optics like diffractive optical elements. However, extant-metasurface-facilitated structured light exhibits sub-optimal performance in downstream tasks, due to heuristic design patterns such as periodic dots that do not consider the objectives of the end application. Here we present 360 degrees structured light, driven by learned metasurfaces. We propose a differentiable framework that encompasses a computationally efficient 180 degrees wave propagation model and a task-specific reconstructor, and exploits both transmission and reflection channels of the metasurface. Leveraging a first-order optimizer within our differentiable framework, we optimize the metasurface design, thereby realizing 360 degrees structured light. We have utilized 360 degrees structured light for holographic light projection and three-dimensional imaging. Specifically, we demonstrate the first 360 degrees light projection of complex patterns, enabled by our propagation model that can be computationally evaluated 50,000x faster than the Rayleigh-Sommerfeld propagation. For three-dimensional imaging, we improve the depth-estimation accuracy by 5.09x in root-mean-square error compared with heuristically designed structured light. Such 360 degrees structured light promises robust 360 degrees imaging and display for robotics, extended-reality systems and human-computer interactions. A single-metasurface-based holographic light projection covering the whole 360 degrees field of view is realized by optimizing the metasurface design through a neural network and applying 360 degrees structured light for holographic light projection and three-dimensional imaging.
Keyword:
RAYLEIGH-SOMMERFELD
PHASE
KIRCHHOFF
期刊
IF:
32.9
论文数:
4.3K
被引数:
6.1W
机构
暂无机构信息
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