Reconstruction of Non-Line-of-Sight Depth Data Using Genetic Algorithm-Lucy-Richardson Based on Time of Flight Camera

Yujie Fang; Xia Wang; Binghua Su

doi:10.3788/AOS230870

Acta Optica Sinica, Volume. 43, Issue 21, 2111002(2023)

Reconstruction of Non-Line-of-Sight Depth Data Using Genetic Algorithm-Lucy-Richardson Based on Time of Flight Camera

Yujie Fang^1,2,3, Xia Wang^1,2,3、*, and Binghua Su^2,3

¹Key Laboratory of Optoelectronic Imaging Technology and System, Ministry of Education, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China

²Beijing Institute of Technology, Zhuhai 519085, Guangdong , China

³Key Laboratory of Intelligent Detection in Complex Environment of Aerospace, Land, and Sea , Zhuhai 519085, Guangdong , China

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Figures & Tables(12)

Fig. 1. Influence of surface relay characteristics of materials on non-line-of-sight (NLOS) imaging

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Fig. 2. Flow chart of target reconstruction in NLOS imaging

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Fig. 3. Experimental scenes and their locations

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Fig. 4. Measured targets and their corresponding depth images collected by flat mirror

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Fig. 5. Scattering characteristics of PP plate and PMMA plate and raw depth data collected from different material relay surfaces. (a) PP plate and part of its BRDF curve; (b) PMMA plate and part of its BRDF curve; (c) mirror; (d) ceramic tile; (e) PP plate; (d) PMMA plate

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Fig. 6. Fitness curves of approximate optical model solutions for three materials

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Fig. 7. Approximate solution for relay surface obtained by genetic algorithm. (a) Approximate solution for optical properties of ceramic tile; (b) approximate solution for optical properties of PP plate; (c) approximate solution for optical properties of PMMA plate

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Fig. 8. Row depth data, average data, error data, and reconstruction results under three sizes of $f_{b s}$ characteristics with different targets using PP plate as relay surface. (a) Gypsum cone; (b) smooth plastics; (c) natural complex scenes

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Fig. 9. Row depth data, average data, error data, and reconstruction results under three sizes of $f_{b s}$ characteristics with different targets using PMMA plate as relay surface. (a) Gypsum cone; (b) smooth plastics; (c) natural complex scenes

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Table 1. Basic parameter setting for experimental scenario
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Table 1. Basic parameter setting for experimental scenario
Parameter Resolution /pixel Modulation /MHz
Illumination power /W
Depth accuracy /mm Target size /cm
Focal length /mm
Value 320×240
46
55
Avg 8 5 20×20 22

Table 2. Mean square error after NLOS image reconstruction based on PP plate relay surface
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Table 2. Mean square error after NLOS image reconstruction based on PP plate relay surface
Raw data Denoised 7×7 model 10×10 model 15×15 model
Gypsum cone 0.0353 0.0194 0.0172 0.0187 0.0105
Smooth plastics 0.0463 0.0352 0.0094 0.0105 0.0103
Natural complex scenes 0.0593 0.0491 0.0193 0.0195 0.0253

Table 3. Mean square error after NLOS image reconstruction based on PMMA plate relay surface
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Table 3. Mean square error after NLOS image reconstruction based on PMMA plate relay surface
Raw data Denoised 7×7 model 10×10 model 15×15 model
Gypsum cone 0.0246 0.0169 0.0075 0.0072 0.0074
Smooth plastics 0.0342 0.0207 0.0079 0.0105 0.0078
Natural complex scenes 0.0562 0.0241 0.0074 0.0075 0.0074

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Yujie Fang, Xia Wang, Binghua Su. Reconstruction of Non-Line-of-Sight Depth Data Using Genetic Algorithm-Lucy-Richardson Based on Time of Flight Camera[J]. Acta Optica Sinica, 2023, 43(21): 2111002

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Paper Information

Category: Imaging Systems

Received: Apr. 24, 2023

Accepted: Jun. 14, 2023

Published Online: Nov. 16, 2023

The Author Email: Wang Xia (angelniuniu@bit.edu.cn)

DOI:10.3788/AOS230870

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Basic parameter setting for experimental scenario

Table 1. Basic parameter setting for experimental scenario

Table 2. Mean square error after NLOS image reconstruction based on PP plate relay surface

Table 2. Mean square error after NLOS image reconstruction based on PP plate relay surface

Table 3. Mean square error after NLOS image reconstruction based on PMMA plate relay surface

Table 3. Mean square error after NLOS image reconstruction based on PMMA plate relay surface