Omnidirectional Ring Structured Light Noise Filtering Based On DCGAN Network And Autoencoder

Wenhao Li, Tong Jia, Qiusheng Chen, Yunhe Wu, Jiang Wang, Junwen Huang
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Abstract

The omnidirectional ring structured light depth perception system can project a 360-degree structured light.However, due to the influence of ambient light, refraction and other noise factors, it is easy to cause false detection of structured light. Therefore, denoising plays an important role in the omnidirectional ring structured light depth perception system.Firstly, this paper uses the DCGAN network to generate more data sets due to the lack of data sets. Secondly, based on the above data sets, this paper uses the autoencoder network to denoise the ring structured light. Experiments show that by using a combination of DCGAN and autoencoder network for denoising, the structured light’s noise is lesstherefore more robust to the surrounding environment compared to other methods.
基于DCGAN网络和自编码器的全向环形结构光噪声滤波
全向环形结构光深度感知系统可投射360度结构光。但由于环境光、折射等噪声因素的影响,容易造成结构光的误检。因此,去噪在全向环形结构光深度感知系统中起着重要的作用。首先,由于数据集不足,本文利用DCGAN网络生成更多的数据集。其次,在上述数据集的基础上,采用自编码器网络对环形结构光进行降噪。实验表明,采用DCGAN和自编码器网络相结合的方法去噪,结构光的噪声较小,对周围环境的鲁棒性优于其他方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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