Computationally efficient classification of human transport mode using micro-Doppler signatures

Guillaume Garreau; Nicoletta Nicolaou; Charalambos Andreou; Cyrille D'Urbal; Guillermo Stuarts; Julius Georgiou

doi:10.1109/CISS.2011.5766136

Computationally efficient classification of human transport mode using micro-Doppler signatures

Guillaume Garreau
, Nicoletta Nicolaou
, Charalambos Andreou
, Cyrille D'Urbal
, Guillermo Stuarts
, Julius Georgiou

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper we present a micro-Doppler (mD) system and a computationally efficient classifier for the purpose of distinguishing different means of transport for human beings (pedestrians, inline skaters and cyclists) based on their mD time-frequency signatures. Accuracies as high as 97% are obtained while keeping the overall computational cost low.

Original language	English
Title of host publication	2011 45th Annual Conference on Information Sciences and Systems, CISS 2011
DOIs	https://doi.org/10.1109/CISS.2011.5766136
Publication status	Published - 6 Jun 2011
Externally published	Yes
Event	2011 45th Annual Conference on Information Sciences and Systems, CISS 2011 - Baltimore, MD, United States Duration: 23 Mar 2011 → 25 Mar 2011

Conference

Conference	2011 45th Annual Conference on Information Sciences and Systems, CISS 2011
Country/Territory	United States
City	Baltimore, MD
Period	23/03/11 → 25/03/11

Keywords

Micro-Doppler
spectrogram
standard deviation
transport mode
ultrasonic device

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10.1109/CISS.2011.5766136

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@inproceedings{92bed50830514e7cb25b14831034360a,

title = "Computationally efficient classification of human transport mode using micro-Doppler signatures",

abstract = "In this paper we present a micro-Doppler (mD) system and a computationally efficient classifier for the purpose of distinguishing different means of transport for human beings (pedestrians, inline skaters and cyclists) based on their mD time-frequency signatures. Accuracies as high as 97\% are obtained while keeping the overall computational cost low.",

keywords = "Micro-Doppler, spectrogram, standard deviation, transport mode, ultrasonic device",

author = "Guillaume Garreau and Nicoletta Nicolaou and Charalambos Andreou and Cyrille D'Urbal and Guillermo Stuarts and Julius Georgiou",

year = "2011",

month = jun,

day = "6",

doi = "10.1109/CISS.2011.5766136",

language = "English",

isbn = "9781424498475",

booktitle = "2011 45th Annual Conference on Information Sciences and Systems, CISS 2011",

note = "2011 45th Annual Conference on Information Sciences and Systems, CISS 2011 ; Conference date: 23-03-2011 Through 25-03-2011",

}

Garreau, G, Nicolaou, N, Andreou, C, D'Urbal, C, Stuarts, G & Georgiou, J 2011, Computationally efficient classification of human transport mode using micro-Doppler signatures. in 2011 45th Annual Conference on Information Sciences and Systems, CISS 2011., 5766136, 2011 45th Annual Conference on Information Sciences and Systems, CISS 2011, Baltimore, MD, United States, 23/03/11. https://doi.org/10.1109/CISS.2011.5766136

TY - GEN

T1 - Computationally efficient classification of human transport mode using micro-Doppler signatures

AU - Garreau, Guillaume

AU - Nicolaou, Nicoletta

AU - Andreou, Charalambos

AU - D'Urbal, Cyrille

AU - Stuarts, Guillermo

AU - Georgiou, Julius

PY - 2011/6/6

Y1 - 2011/6/6

N2 - In this paper we present a micro-Doppler (mD) system and a computationally efficient classifier for the purpose of distinguishing different means of transport for human beings (pedestrians, inline skaters and cyclists) based on their mD time-frequency signatures. Accuracies as high as 97% are obtained while keeping the overall computational cost low.

AB - In this paper we present a micro-Doppler (mD) system and a computationally efficient classifier for the purpose of distinguishing different means of transport for human beings (pedestrians, inline skaters and cyclists) based on their mD time-frequency signatures. Accuracies as high as 97% are obtained while keeping the overall computational cost low.

KW - Micro-Doppler

KW - spectrogram

KW - standard deviation

KW - transport mode

KW - ultrasonic device

UR - https://www.scopus.com/pages/publications/79957872465

U2 - 10.1109/CISS.2011.5766136

DO - 10.1109/CISS.2011.5766136

M3 - Conference contribution

AN - SCOPUS:79957872465

SN - 9781424498475

BT - 2011 45th Annual Conference on Information Sciences and Systems, CISS 2011

T2 - 2011 45th Annual Conference on Information Sciences and Systems, CISS 2011

Y2 - 23 March 2011 through 25 March 2011

ER -

Computationally efficient classification of human transport mode using micro-Doppler signatures

Abstract

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Keywords

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