Fooling Polarization-based Vision using Locally Controllable Polarizing Projection

Fuente: arXiv
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Hauptverfasser: Li, Zhuoxiao, Zhong, Zhihang, Nobuhara, Shohei, Nishino, Ko, Zheng, Yinqiang
Format: Preprint
Veröffentlicht: 2023
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author Li, Zhuoxiao
Zhong, Zhihang
Nobuhara, Shohei
Nishino, Ko
Zheng, Yinqiang
author_facet Li, Zhuoxiao
Zhong, Zhihang
Nobuhara, Shohei
Nishino, Ko
Zheng, Yinqiang
contents Polarization is a fundamental property of light that encodes abundant information regarding surface shape, material, illumination and viewing geometry. The computer vision community has witnessed a blossom of polarization-based vision applications, such as reflection removal, shape-from-polarization, transparent object segmentation and color constancy, partially due to the emergence of single-chip mono/color polarization sensors that make polarization data acquisition easier than ever. However, is polarization-based vision vulnerable to adversarial attacks? If so, is that possible to realize these adversarial attacks in the physical world, without being perceived by human eyes? In this paper, we warn the community of the vulnerability of polarization-based vision, which can be more serious than RGB-based vision. By adapting a commercial LCD projector, we achieve locally controllable polarizing projection, which is successfully utilized to fool state-of-the-art polarization-based vision algorithms for glass segmentation and color constancy. Compared with existing physical attacks on RGB-based vision, which always suffer from the trade-off between attack efficacy and eye conceivability, the adversarial attackers based on polarizing projection are contact-free and visually imperceptible, since naked human eyes can rarely perceive the difference of viciously manipulated polarizing light and ordinary illumination. This poses unprecedented risks on polarization-based vision, both in the monochromatic and trichromatic domain, for which due attentions should be paid and counter measures be considered.
format Preprint
id arxiv_https___arxiv_org_abs_2303_17890
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Fooling Polarization-based Vision using Locally Controllable Polarizing Projection
Li, Zhuoxiao
Zhong, Zhihang
Nobuhara, Shohei
Nishino, Ko
Zheng, Yinqiang
Computer Vision and Pattern Recognition
Polarization is a fundamental property of light that encodes abundant information regarding surface shape, material, illumination and viewing geometry. The computer vision community has witnessed a blossom of polarization-based vision applications, such as reflection removal, shape-from-polarization, transparent object segmentation and color constancy, partially due to the emergence of single-chip mono/color polarization sensors that make polarization data acquisition easier than ever. However, is polarization-based vision vulnerable to adversarial attacks? If so, is that possible to realize these adversarial attacks in the physical world, without being perceived by human eyes? In this paper, we warn the community of the vulnerability of polarization-based vision, which can be more serious than RGB-based vision. By adapting a commercial LCD projector, we achieve locally controllable polarizing projection, which is successfully utilized to fool state-of-the-art polarization-based vision algorithms for glass segmentation and color constancy. Compared with existing physical attacks on RGB-based vision, which always suffer from the trade-off between attack efficacy and eye conceivability, the adversarial attackers based on polarizing projection are contact-free and visually imperceptible, since naked human eyes can rarely perceive the difference of viciously manipulated polarizing light and ordinary illumination. This poses unprecedented risks on polarization-based vision, both in the monochromatic and trichromatic domain, for which due attentions should be paid and counter measures be considered.
title Fooling Polarization-based Vision using Locally Controllable Polarizing Projection
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2303.17890