An Overview of Human Pose Estimation Based on Wireless Signals
Human pose estimation holds tremendous potential in fields such as human-computer interaction, motion capture, and virtual reality, making it a focus in human perception research. However, optical image-based pose estimation methods are often limited by lighting conditions and privacy concerns. Ther...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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China Science Publishing & Media Ltd. (CSPM)
2025-02-01
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| Series: | Leida xuebao |
| Subjects: | |
| Online Access: | https://radars.ac.cn/cn/article/doi/10.12000/JR24189 |
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| author | Yan CHEN Rui ZHANG Yadong LI Ruiyuan SONG Ruixu GENG Hanqin GONG Binquan WANG Dongheng ZHANG Yang HU |
| author_facet | Yan CHEN Rui ZHANG Yadong LI Ruiyuan SONG Ruixu GENG Hanqin GONG Binquan WANG Dongheng ZHANG Yang HU |
| author_sort | Yan CHEN |
| collection | DOAJ |
| description | Human pose estimation holds tremendous potential in fields such as human-computer interaction, motion capture, and virtual reality, making it a focus in human perception research. However, optical image-based pose estimation methods are often limited by lighting conditions and privacy concerns. Therefore, the use of wireless signals that can operate under various lighting conditions and obstructions while ensuring privacy is gaining increasing attention for human pose estimation. Wireless signal-based pose estimation technologies can be categorized into high-frequency and low-frequency methods. These methods differ in their hardware systems, signal characteristics, noise processing, and deep learning algorithm design based on the signal frequency used. This paper highlights research advancements and notable works in human pose reconstruction using millimeter-wave radar, through-wall radar, and WiFi. It analyzes the advantages and limitations of each signal type and explores potential research challenges and future developments in the field. |
| format | Article |
| id | doaj-art-7ac38599809d4894bddbf0e8e8510be9 |
| institution | Kabale University |
| issn | 2095-283X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | China Science Publishing & Media Ltd. (CSPM) |
| record_format | Article |
| series | Leida xuebao |
| spelling | doaj-art-7ac38599809d4894bddbf0e8e8510be92025-01-22T06:12:26ZengChina Science Publishing & Media Ltd. (CSPM)Leida xuebao2095-283X2025-02-0114122924710.12000/JR24189R24189An Overview of Human Pose Estimation Based on Wireless SignalsYan CHEN0Rui ZHANG1Yadong LI2Ruiyuan SONG3Ruixu GENG4Hanqin GONG5Binquan WANG6Dongheng ZHANG7Yang HU8School of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, ChinaSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, ChinaDepartment of Electrical and Computer Engineering, University of Washington, Seattle 98195, United StatesSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, ChinaSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, ChinaSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, ChinaSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, ChinaSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, ChinaSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, ChinaHuman pose estimation holds tremendous potential in fields such as human-computer interaction, motion capture, and virtual reality, making it a focus in human perception research. However, optical image-based pose estimation methods are often limited by lighting conditions and privacy concerns. Therefore, the use of wireless signals that can operate under various lighting conditions and obstructions while ensuring privacy is gaining increasing attention for human pose estimation. Wireless signal-based pose estimation technologies can be categorized into high-frequency and low-frequency methods. These methods differ in their hardware systems, signal characteristics, noise processing, and deep learning algorithm design based on the signal frequency used. This paper highlights research advancements and notable works in human pose reconstruction using millimeter-wave radar, through-wall radar, and WiFi. It analyzes the advantages and limitations of each signal type and explores potential research challenges and future developments in the field.https://radars.ac.cn/cn/article/doi/10.12000/JR24189human pose estimationwireless sensingdeep learningmillimeter-wave radarthrough-wall radar (twr)wifi |
| spellingShingle | Yan CHEN Rui ZHANG Yadong LI Ruiyuan SONG Ruixu GENG Hanqin GONG Binquan WANG Dongheng ZHANG Yang HU An Overview of Human Pose Estimation Based on Wireless Signals Leida xuebao human pose estimation wireless sensing deep learning millimeter-wave radar through-wall radar (twr) wifi |
| title | An Overview of Human Pose Estimation Based on Wireless Signals |
| title_full | An Overview of Human Pose Estimation Based on Wireless Signals |
| title_fullStr | An Overview of Human Pose Estimation Based on Wireless Signals |
| title_full_unstemmed | An Overview of Human Pose Estimation Based on Wireless Signals |
| title_short | An Overview of Human Pose Estimation Based on Wireless Signals |
| title_sort | overview of human pose estimation based on wireless signals |
| topic | human pose estimation wireless sensing deep learning millimeter-wave radar through-wall radar (twr) wifi |
| url | https://radars.ac.cn/cn/article/doi/10.12000/JR24189 |
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