Neuromorphic Event-based Space-Time Template Action Recognition

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

Research output: Contribution to conferencePaper

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.

Conference

ConferenceIrish Machine Vision and Image Processing Conference
Abbreviated titleIMVIP
CountryUnited Kingdom
Period29/08/1831/08/18

Fingerprint

Hardware
Template matching
Image processing
Assisted living

Keywords

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

Cite this

Harrigan, S., Kerr, D., Coleman, S., Yogarajah, P., Fang, Z., & Wu, C. (2018). Neuromorphic Event-based Space-Time Template Action Recognition. Paper presented at Irish Machine Vision and Image Processing Conference, United Kingdom.
Harrigan, Shane ; Kerr, Dermot ; Coleman, Sonya ; Yogarajah, Pratheepan ; Fang, Zheng ; Wu, Chengdong. / Neuromorphic Event-based Space-Time Template Action Recognition. Paper presented at Irish Machine Vision and Image Processing Conference, United Kingdom.
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author = "Shane Harrigan and Dermot Kerr and Sonya Coleman and Pratheepan Yogarajah and Zheng Fang and Chengdong Wu",
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Harrigan, S, Kerr, D, Coleman, S, Yogarajah, P, Fang, Z & Wu, C 2018, 'Neuromorphic Event-based Space-Time Template Action Recognition' Paper presented at Irish Machine Vision and Image Processing Conference, United Kingdom, 29/08/18 - 31/08/18, .

Neuromorphic Event-based Space-Time Template Action Recognition. / Harrigan, Shane; Kerr, Dermot; Coleman, Sonya; Yogarajah, Pratheepan; Fang, Zheng; Wu, Chengdong.

2018. Paper presented at Irish Machine Vision and Image Processing Conference, United Kingdom.

Research output: Contribution to conferencePaper

TY - CONF

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

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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

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M3 - Paper

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Harrigan S, Kerr D, Coleman S, Yogarajah P, Fang Z, Wu C. Neuromorphic Event-based Space-Time Template Action Recognition. 2018. Paper presented at Irish Machine Vision and Image Processing Conference, United Kingdom.