Įxisting 3D imaging technologies can be divided into two major categories: active and passive techniques.

Currently, the 3D reconstruction technique has drawn widespread attention and achieved great progress in face recognition, industrial inspection, autonomous driving, and digital imaging. With advancements in new sensors, data transmission, and storage, more information about the light field such as phase, polarization, and spectral information can be efficiently detected and recorded, which helps to construct a functional relationship between the reflected light information and the contour of the object surface to obtain 3D information. In this paper, the fundamental principles behind these technologies will be elucidated, experimental results will be presented to demonstrate the capabilities and limitations of these popular technologies, and finally, our perspectives on the remaining challenges of the polarization 3D imaging technology will be presented.Īs an important approach for humans to record and perceive environmental information, traditional optoelectronic imaging techniques are increasingly ineffective due to the loss of high-dimensional information.

Additionally, other problems and related solutions in polarization 3D imaging technology are also investigated. Meanwhile, some polarization 3D imaging techniques attempt to extend experimental objects to complex specific targets and scenarios through a learning-based approach. Over the past few decades, many shape from polarization techniques have been proposed to address the ambiguity issues, i.e., high-precision normal acquisition. The ambiguity in the normal obtained by the polarization characteristics of the target’s specular or diffuse reflected light limits the development of polarization 3D imaging technology. Polarization three-dimensional (3D) imaging technology has received extensive attention in recent years because of its advantages of high accuracy, long detection distance, simplicity, and low cost.

2School of Optoelectronic Engineering, Xidian University, Xi’an, China.

1Hangzhou Institute of Technology, Xidian University, Hangzhou, China.

Xuan Li 1,2, Zhiqiang Liu 1, Yudong Cai 1,2, Cunying Pan 1, Jiawei Song 1, Jinshou Wang 1 and Xiaopeng Shao 1,2*

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