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.
|Publication status||Published - 29 Aug 2018|
|Event||Irish Machine Vision and Image Processing Conference - Belfast, United Kingdom|
Duration: 29 Aug 2018 → 31 Aug 2018
|Conference||Irish Machine Vision and Image Processing Conference|
|Period||29/08/18 → 31/08/18|
- neuromorphic image processing
- space-time, ageing-in-place
- action detection
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.