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Main Authors: Chen, Cheng, Ohta, Shoki, Nishio, Takayuki, Bennis, Mehdi, Park, Jihong, Wahib, Mohamed
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2305.05385
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author Chen, Cheng
Ohta, Shoki
Nishio, Takayuki
Bennis, Mehdi
Park, Jihong
Wahib, Mohamed
author_facet Chen, Cheng
Ohta, Shoki
Nishio, Takayuki
Bennis, Mehdi
Park, Jihong
Wahib, Mohamed
contents Introducing CSI-Inpainter, a pioneering approach for occlusion removal using Channel State Information (CSI) time sequences, this work propels the application of wireless signal processing into the realm of visual scene recovery. Departing from traditional occlusion removal, CSI-Inpainter leverages CSI data to construct and refine obscured visual elements in a scene, facilitating recovery independent of lighting conditions. Validated through comprehensive testing in both office and industrial environments, CSI-Inpainter demonstrates a robust capacity for discerning and reconstructing occluded segments, establishing a new frontier for obstacle removal. This first-of-its-kind framework offers a transformative perspective on how environmental visual information can be extracted from CSI, thereby broadening the scope for computer vision applications in everyday contexts.
format Preprint
id arxiv_https___arxiv_org_abs_2305_05385
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle CSI-Inpainter: Enabling Visual Scene Recovery from CSI Time Sequences for Occlusion Removal
Chen, Cheng
Ohta, Shoki
Nishio, Takayuki
Bennis, Mehdi
Park, Jihong
Wahib, Mohamed
Image and Video Processing
Introducing CSI-Inpainter, a pioneering approach for occlusion removal using Channel State Information (CSI) time sequences, this work propels the application of wireless signal processing into the realm of visual scene recovery. Departing from traditional occlusion removal, CSI-Inpainter leverages CSI data to construct and refine obscured visual elements in a scene, facilitating recovery independent of lighting conditions. Validated through comprehensive testing in both office and industrial environments, CSI-Inpainter demonstrates a robust capacity for discerning and reconstructing occluded segments, establishing a new frontier for obstacle removal. This first-of-its-kind framework offers a transformative perspective on how environmental visual information can be extracted from CSI, thereby broadening the scope for computer vision applications in everyday contexts.
title CSI-Inpainter: Enabling Visual Scene Recovery from CSI Time Sequences for Occlusion Removal
topic Image and Video Processing
url https://arxiv.org/abs/2305.05385