RaGeoSense for smart home gesture recognition using sparse millimeter wave radar point clouds Article Swipe
Honghong Chen
,
Xiangyu Wang
,
Zhanjun Hao
,
Yan Lu
,
Jingyu Li
,
Haozhe Zhang
,
Ben Xi
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-025-00065-8
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-025-00065-8
With the growing demand for contactless human-computer interaction in the smart home field, gesture recognition technology shows great market potential. In this paper, a sparse millimeter wave point cloud-based gesture recognition system, RaGeoSense, is proposed, which is designed for smart home scenarios. RaGeoSense effectively improves the recognition performance and system robustness by combining multiple advanced signal processing and deep learning methods. Firstly, the system adopts three methods, namely K-mean clustering straight-through filtering, frame difference filtering and median filtering, to reduce the noise of the raw millimeter wave data, which significantly improves the quality of the point cloud data. Subsequently, the generated point cloud data are processed with sliding sequence sampling and point cloud tiling to extract the spatio-temporal features of the action. To further improve the classification performance, the system proposes an integrated model architecture that combines GBDT and XGBoost for efficient extraction of nonlinear features, and utilizes LSTM gated loop units to classify the gesture sequences, thus realizing the accurate recognition of eight different one-arm gestures. The experimental results show that RaGeoSense performs well at different distances, angles and movement speeds, with an average recognition rate of 95.2%, which is almost unaffected by the differences in personnel and has a certain degree of anti-interference ability.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41598-025-00065-8
- https://www.nature.com/articles/s41598-025-00065-8.pdf
- OA Status
- gold
- Cited By
- 1
- References
- 46
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4410010261
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4410010261Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1038/s41598-025-00065-8Digital Object Identifier
- Title
-
RaGeoSense for smart home gesture recognition using sparse millimeter wave radar point cloudsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-05-01Full publication date if available
- Authors
-
Honghong Chen, Xiangyu Wang, Zhanjun Hao, Yan Lu, Jingyu Li, Haozhe Zhang, Ben XiList of authors in order
- Landing page
-
https://doi.org/10.1038/s41598-025-00065-8Publisher landing page
- PDF URL
-
https://www.nature.com/articles/s41598-025-00065-8.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.nature.com/articles/s41598-025-00065-8.pdfDirect OA link when available
- Concepts
-
Point cloud, Computer science, Extremely high frequency, Gesture, Radar, Gesture recognition, Point (geometry), Artificial intelligence, Pattern recognition (psychology), Telecommunications, Mathematics, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
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46Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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