From Signal to Image: Capturing Fine-Grained Human Poses With Commodity Wi-Fi

Guo, Lingchao; Lu, Zhaoming; Wen, Xiangming; Zhou, Shuang; Han, Zijun

doi:10.1109/lcomm.2019.2961890

Cited by 43 publications

(64 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To the best of our knowledge, this is the first time CSI-to-image conversion has been achieved using GANs. From the perspective of CSIto-image conversion without GANs, a few related studies have been conducted [1], [2]. Wi2Vi [1] uses the video recovered by CSI when a security camera is disabled owing to power failure, malfunction, or attack.…”

Section: Introductionmentioning

confidence: 99%

“…Under critical conditions, Wi2Vi generates an image by superimposing the detected user onto the background image. [2] has successfully generated pose images generated from skeletons from CSI by learning the relationship between the skeleton model of human posture and CSI. [1], [2] are application-specific approaches, using application-specific information such as background images and skeleton models.…”

Section: Introductionmentioning

confidence: 99%

“…[2] has successfully generated pose images generated from skeletons from CSI by learning the relationship between the skeleton model of human posture and CSI. [1], [2] are application-specific approaches, using application-specific information such as background images and skeleton models. By contrast, the present study focuses on a general-purpose CSI-to-image conversion method using GANs.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

CSI2Image: Image Reconstruction From Channel State Information Using Generative Adversarial Networks

et al. 2021

View full text Add to dashboard Cite

This study aims to determine the upper limit of the wireless sensing capability of acquiring physical space information. This is a challenging objective because, at present, wireless sensing studies continue to succeed in acquiring novel phenomena. Thus, although we have still not obtained a complete answer, a step is taken toward it herein. To achieve this, CSI2Image, a novel channel state information (CSI)-to-image conversion method based on generative adversarial networks (GANs), is proposed. The type of physical information acquired using wireless sensing can be estimated by checking whether the reconstructed image captures the desired physical space information. We demonstrate three types of learning methods: generator-only learning, GAN-only learning, and hybrid learning. Evaluating the performance of CSI2Image is difficult because both the clarity of the image and the presence of the desired physical space information must be evaluated. To solve this problem, we propose a quantitative evaluation methodology using an image-based object detection system. CSI2Image was implemented using IEEE 802.11ac compressed CSI, and the evaluation results show that CSI2Image successfully reconstructs images. The results demonstrate that generator-only learning is sufficient for simple wireless sensing problems; however, in complex wireless sensing problems, GANs are essential for reconstructing generalized images with more accurate physical space information. INDEX TERMS wireless sensing, channel state information, deep learning, generative adversarial networks, image reconstruction

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

CSI2Image: Image Reconstruction From Channel State Information Using Generative Adversarial Networks

et al. 2021

View full text Add to dashboard Cite

show abstract

“…These days, with the continuous development of high precision, cost-effective computer imaging hardware equipment and corresponding auxiliary detection algorithm, real-time target human tracking technology [1]- [8] has become a research hotspot in various fields such as interactive video games, military, robotic, etc. Human tracking is the process of locating moving targets by performing tracking algorithms and analyzing that trajectory in many applications over sequential video frames [9]- [12] The models of the target could be a single human or multiple humans based on different applications.…”

Section: Introductionmentioning

confidence: 99%

Real-time Target Human Tracking using Camshift and LucasKanade Optical Flow Algorithm

Nguyen¹,

Nguyen²,

Bui³

et al. 2021

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

In this paper, a novel is proposed for real-time tracking human targets in cases of high influence from complexity environment with a normal camera. Firstly, based on Oriented FAST and Rotated BRIEF features, the Lucas-Kanade Optical Flow algorithm is used to track reliable keypoints. This method represents a valuable performance to decline the effect of the illumination or displacement of human targets. Secondly, the area of the human target in the frame is determined more precise by using the Camshift algorithm. Compared to the existing approaches, the proposed method has some merits to some extents including rapid calculations in implementation, high accuracy in case of similar objects detection, the ability to deploy easily on mobile devices. Finally, the effectiveness of the proposed tracking algorithm is demonstrated via experimental results.

show abstract

“…In LA, the initial stage of Wi-Fi process enables user for complete competitive analysis for determining the probability of occurrence of each node. This leads in decisive dead spots that avoids slow and unstable connections [14][15][16]. The inter-interference region can cause decrease in deployment efficiency with more IT investment.…”

Section: Introductionmentioning

confidence: 99%

Cross Layer Design for Wi-Fi Sensor Network Handling Static and Dynamic Environment Using Local Automate Based Autonomic Network Architecture

Sanjay¹,

Shaila²,

Venugopal

2021

SN COMPUT. SCI.

View full text Add to dashboard Cite

From Signal to Image: Capturing Fine-Grained Human Poses With Commodity Wi-Fi

Cited by 43 publications

References 9 publications

CSI2Image: Image Reconstruction From Channel State Information Using Generative Adversarial Networks

CSI2Image: Image Reconstruction From Channel State Information Using Generative Adversarial Networks

Real-time Target Human Tracking using Camshift and LucasKanade Optical Flow Algorithm

Cross Layer Design for Wi-Fi Sensor Network Handling Static and Dynamic Environment Using Local Automate Based Autonomic Network Architecture

Contact Info

Product

Resources

About