Neuromorphic Event-based Space-Time Template Action Recognition

Shane Harrigan; Dermot Kerr; Sonya Coleman; Pratheepan Yogarajah; Zheng Fang; Chengdong Wu

Neuromorphic Event-based Space-Time Template Action Recognition

Shane Harrigan, Dermot Kerr, Sonya Coleman, Pratheepan Yogarajah, Zheng Fang, Chengdong Wu

Research output: Contribution to conference › Paper › peer-review

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Abstract

Neuromorphic vision hardware enables observed actions to be reduced to a series of spike trains; these trains contain unique properties relevant to observed actions. This paper presents an approach to event-based image processing which allows for the detection of specific fine grain actions through the adoption of template matching alongside neuromorphic hardware. The proposed approach was applied to the detection of breathing actions in an ambient assisted living (AAL) environment, this involved the detection of shallow, normal and heavy breathing for multiple participants using a single template. The results gained suggest that this approach could be useful when deployed in an AAL environment.

Original language	English
Publication status	Published (in print/issue) - 29 Aug 2018
Event	Irish Machine Vision and Image Processing Conference - Belfast, United Kingdom Duration: 29 Aug 2018 → 31 Aug 2018

Conference

Conference	Irish Machine Vision and Image Processing Conference
Abbreviated title	IMVIP
Country/Territory	United Kingdom
Period	29/08/18 → 31/08/18

Keywords

event-based
neuromorphic image processing
space-time, ageing-in-place
action detection

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imvip2018_SHarrigan_acceptedAuthor Accepted Manuscript, 981 KB

Cite this

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title = "Neuromorphic Event-based Space-Time Template Action Recognition",

abstract = "Neuromorphic vision hardware enables observed actions to be reduced to a series of spike trains; these trains contain unique properties relevant to observed actions. This paper presents an approach to event-based image processing which allows for the detection of specific fine grain actions through the adoption of template matching alongside neuromorphic hardware. The proposed approach was applied to the detection of breathing actions in an ambient assisted living (AAL) environment, this involved the detection of shallow, normal and heavy breathing for multiple participants using a single template. The results gained suggest that this approach could be useful when deployed in an AAL environment.",

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author = "Shane Harrigan and Dermot Kerr and Sonya Coleman and Pratheepan Yogarajah and Zheng Fang and Chengdong Wu",

year = "2018",

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note = "Irish Machine Vision and Image Processing Conference, IMVIP ; Conference date: 29-08-2018 Through 31-08-2018",

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T1 - Neuromorphic Event-based Space-Time Template Action Recognition

AU - Harrigan, Shane

AU - Kerr, Dermot

AU - Coleman, Sonya

AU - Yogarajah, Pratheepan

AU - Fang, Zheng

AU - Wu, Chengdong

PY - 2018/8/29

Y1 - 2018/8/29

N2 - Neuromorphic vision hardware enables observed actions to be reduced to a series of spike trains; these trains contain unique properties relevant to observed actions. This paper presents an approach to event-based image processing which allows for the detection of specific fine grain actions through the adoption of template matching alongside neuromorphic hardware. The proposed approach was applied to the detection of breathing actions in an ambient assisted living (AAL) environment, this involved the detection of shallow, normal and heavy breathing for multiple participants using a single template. The results gained suggest that this approach could be useful when deployed in an AAL environment.

AB - Neuromorphic vision hardware enables observed actions to be reduced to a series of spike trains; these trains contain unique properties relevant to observed actions. This paper presents an approach to event-based image processing which allows for the detection of specific fine grain actions through the adoption of template matching alongside neuromorphic hardware. The proposed approach was applied to the detection of breathing actions in an ambient assisted living (AAL) environment, this involved the detection of shallow, normal and heavy breathing for multiple participants using a single template. The results gained suggest that this approach could be useful when deployed in an AAL environment.

KW - event-based

KW - neuromorphic image processing

KW - space-time, ageing-in-place

KW - action detection

UR - https://iprcs.scss.tcd.ie/IMVIP.html

M3 - Paper

T2 - Irish Machine Vision and Image Processing Conference

Y2 - 29 August 2018 through 31 August 2018

ER -

Neuromorphic Event-based Space-Time Template Action Recognition

Abstract

Conference

Keywords

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