Neuromorphic Event-based Space-Time Template Action Recognition

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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 languageEnglish
Publication statusPublished - 29 Aug 2018
EventIrish Machine Vision and Image Processing Conference - Belfast, United Kingdom
Duration: 29 Aug 201831 Aug 2018

Conference

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

Keywords

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

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  • 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.