红外与激光工程, 2020, 49 (3): 0303018, 网络出版: 2020-04-22   

深度学习技术在条纹投影三维成像中的应用 下载: 1410次

Application of deep learning technology to fringe projection 3D imaging
作者单位
南京理工大学 电子工程与光电技术学院,江苏 南京 210094
摘要
条纹投影(结构光)三维成像是一种广泛使用的三维成像手段。近年来,集成式的三维传感器发展迅速,特别是基于结构光原理的三维传感器件已逐渐成为高端智能手机必不可少的一个重要传感单元。然而随着应用需求的不断增多,人们对条纹投影三维成像这项技术的效率、精度、稳定性等方面的要求也越来越高。同时近年来,深度学习技术的飞速发展已经为光学成像技术的发展开启了一扇新的大门,并且从这扇大门中人们注意到伴随着人工智能概念的引入,条纹投影技术的发展也正在经历着新的突破。首先简要介绍了条纹投影三维成像的基本理论。随后举例分析通过运用深度学习技术,起初基于物理模型的条纹投影技术也可成为一种在“数据”驱动下实现的技术,而且在这种情况下,它展现出了超越传统算法的潜力。最后从神经网络模型、训练数据、训练方法等方面,讨论该领域面临的挑战与未来的研究方向。
Abstract
Fringe projection(structured light) 3D imaging is a widely used 3D imaging method. In recent years, the integrated three-dimensional sensor has developed rapidly, especially the three-dimensional sensor based on the principle of structured light has gradually become an essential sensor unit for high-end smart phones. However, with the increasing requirements from applications, people have higher and higher requirements on the efficiency, accuracy, stability and other aspects for the fringe projection technique. At the same time, the rapid development of deep learning technology has opened a new door for the development of optical imaging technology, and from this door we notice that with the introduction of the concept of artificial intelligence, the development of fringe projection technology is also experiencing a new breakthrough. In this paper, the basic theory of fringe projection 3D imaging was introduced. Then, by using the deep learning technology, the fringe projection technology based on the physical model can become a technology driven by "data", and in this case, it showed the potential to surpass the traditional algorithm. Finally, the challenges and future research directions in this field from the aspects of neural network model, training data, training methods and so on were discussed.

冯世杰, 左超, 尹维, 陈钱. 深度学习技术在条纹投影三维成像中的应用[J]. 红外与激光工程, 2020, 49(3): 0303018. Shijie Feng, Chao Zuo, Wei Yin, Qian Chen. Application of deep learning technology to fringe projection 3D imaging[J]. Infrared and Laser Engineering, 2020, 49(3): 0303018.

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