Classification of micro-Doppler radar hand-gesture signatures by means of Chebyshev moments

Luca  Pallotta; Michela  Cauli; Carmine Clemente; Francesco Fioranelli; Gaetano  Giunta; Alfonso  Farina

doi:10.1109/MetroAeroSpace51421.2021.9511751

Classification of micro-Doppler radar hand-gesture signatures by means of Chebyshev moments

Luca Pallotta, Michela Cauli, Carmine Clemente, Francesco Fioranelli, Gaetano Giunta, Alfonso Farina

Microwave Sensing, Signals & Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

4 Citations (Scopus)

64 Downloads (Pure)

Abstract

In this paper a method capable of automatically classify radar signals of human hand-gestures exploiting the micro-Doppler signature is designed. In particular, the methodology focuses on the extraction of the Chebyshev moments from the cadence velocity diagram (CVD) of each recorded signal. The algorithm benefits from interesting properties of these moments such as the fact that they are defined on a discrete set and hence computed without approximations, as well as the symmetry property that allows to minimize the computational time. The experiments computed on the challenging real-recorded DopNet dataset show interesting results that confirm the effectiveness of the approach.

Original language	English
Title of host publication	2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)
Publisher	IEEE
Pages	182-187
Number of pages	6
ISBN (Electronic)	978-1-7281-7556-0
ISBN (Print)	978-1-7281-7557-7
DOIs	https://doi.org/10.1109/MetroAeroSpace51421.2021.9511751
Publication status	Published - 2021
Event	2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace) - Naples, Italy Duration: 23 Jun 2021 → 25 Jun 2021

Publication series

Name	2021 IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2021 - Proceedings

Workshop

Workshop	2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)
Country/Territory	Italy
City	Naples
Period	23/06/21 → 25/06/21

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

Automatic target recognition
Hand-gesture recognition
Image moments
Micro-Doppler
Millimeter wave radar

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10.1109/MetroAeroSpace51421.2021.9511751

Classification_of_micro-Doppler_radar_hand-gesture_signatures_by_means_of_Chebyshev_momentsFinal published version, 1.15 MB

Cite this

Pallotta, L., Cauli, M., Clemente, C., Fioranelli, F., Giunta, G., & Farina, A. (2021). Classification of micro-Doppler radar hand-gesture signatures by means of Chebyshev moments. In 2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace) (pp. 182-187). Article 9511751 (2021 IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2021 - Proceedings). IEEE. https://doi.org/10.1109/MetroAeroSpace51421.2021.9511751

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title = "Classification of micro-Doppler radar hand-gesture signatures by means of Chebyshev moments",

abstract = "In this paper a method capable of automatically classify radar signals of human hand-gestures exploiting the micro-Doppler signature is designed. In particular, the methodology focuses on the extraction of the Chebyshev moments from the cadence velocity diagram (CVD) of each recorded signal. The algorithm benefits from interesting properties of these moments such as the fact that they are defined on a discrete set and hence computed without approximations, as well as the symmetry property that allows to minimize the computational time. The experiments computed on the challenging real-recorded DopNet dataset show interesting results that confirm the effectiveness of the approach.",

keywords = "Automatic target recognition, Hand-gesture recognition, Image moments, Micro-Doppler, Millimeter wave radar",

author = "Luca Pallotta and Michela Cauli and Carmine Clemente and Francesco Fioranelli and Gaetano Giunta and Alfonso Farina",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. ; 2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace) ; Conference date: 23-06-2021 Through 25-06-2021",

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isbn = "978-1-7281-7557-7",

series = "2021 IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2021 - Proceedings",

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Pallotta, L, Cauli, M, Clemente, C, Fioranelli, F, Giunta, G & Farina, A 2021, Classification of micro-Doppler radar hand-gesture signatures by means of Chebyshev moments. in 2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)., 9511751, 2021 IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2021 - Proceedings, IEEE, pp. 182-187, 2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace), Naples, Italy, 23/06/21. https://doi.org/10.1109/MetroAeroSpace51421.2021.9511751

Classification of micro-Doppler radar hand-gesture signatures by means of Chebyshev moments. / Pallotta, Luca ; Cauli, Michela ; Clemente, Carmine et al.
2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace). IEEE, 2021. p. 182-187 9511751 (2021 IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2021 - Proceedings).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Cauli, Michela

AU - Clemente, Carmine

AU - Fioranelli, Francesco

AU - Giunta, Gaetano

AU - Farina, Alfonso

N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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N2 - In this paper a method capable of automatically classify radar signals of human hand-gestures exploiting the micro-Doppler signature is designed. In particular, the methodology focuses on the extraction of the Chebyshev moments from the cadence velocity diagram (CVD) of each recorded signal. The algorithm benefits from interesting properties of these moments such as the fact that they are defined on a discrete set and hence computed without approximations, as well as the symmetry property that allows to minimize the computational time. The experiments computed on the challenging real-recorded DopNet dataset show interesting results that confirm the effectiveness of the approach.

AB - In this paper a method capable of automatically classify radar signals of human hand-gestures exploiting the micro-Doppler signature is designed. In particular, the methodology focuses on the extraction of the Chebyshev moments from the cadence velocity diagram (CVD) of each recorded signal. The algorithm benefits from interesting properties of these moments such as the fact that they are defined on a discrete set and hence computed without approximations, as well as the symmetry property that allows to minimize the computational time. The experiments computed on the challenging real-recorded DopNet dataset show interesting results that confirm the effectiveness of the approach.

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Pallotta L, Cauli M, Clemente C, Fioranelli F, Giunta G, Farina A. Classification of micro-Doppler radar hand-gesture signatures by means of Chebyshev moments. In 2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace). IEEE. 2021. p. 182-187. 9511751. (2021 IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2021 - Proceedings). doi: 10.1109/MetroAeroSpace51421.2021.9511751

Classification of micro-Doppler radar hand-gesture signatures by means of Chebyshev moments

Abstract

Publication series

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Bibliographical note

Keywords

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