Challenges and perspectives in neuromorphic-based visual IoT systems and networks

Martini, Maria, Khan, Nabeel, Bi, Yin, Andreopoulos, Yiannis, Saki, Hadi and Shikh-Bahaei, Mohammad (2020) Challenges and perspectives in neuromorphic-based visual IoT systems and networks. In: ICASSP 2020 : 45th International Conference on Acoustics, Speech, and Signal Processing; 04 - 08 May 2020, Barcelona, Spain (held online).

Official URL: https://doi.org/10.1109/ICASSP40776.2020.9054303

Abstract

Neuromorphic sensors, a.k.a. dynamic vision sensors (DVS) or silicon retinas, do not capture full images (frames) at a fixed rate, but asynchronously capture spikes indicating changes of brightness in the scene, following the principles of biological vision and perception in mammals. DVS sensing and processing produces a data representation where the scene can be represented with a very high time resolution with a limited number of bits (an inherent data compression is performed at the time of acquisition). Such representation can be used locally to derive actionable responses and selected parts can be transmitted and then processed in another network location. Due to these features, such sensors represent an excellent choice as visual sensing technology for next-generation Internet-ofThings, e.g. in surveillance, drone technology, and robotics. It is in fact becoming evident that in this framework acquiring, processing, and transmitting frame-based video is inefficient in terms of energy consumption and reaction times, in particular in some scenarios. Hence, we explore here the feasibility of advanced Machine to Machine (M2M) communications systems that directly capture, compress and transmit spike-based visual information to cloud computing services in order to produce content classification or retrieval results with extremely low power and low latency

Official URL:	https://doi.org/10.1109/ICASSP40776.2020.9054303
Item Type:	Conference or Workshop Item (Paper)
Event Title:	ICASSP 2020 : 45th International Conference on Acoustics, Speech, and Signal Processing
Organising Body:	Institute of Electrical and Electronics Engineers
Additional Information:	This work was supported by the Engineering and Physical Sciences Research Council [Grant Numbers: EP/P022715/1, EP/P02243X/1 and EP/P022723 (The Internet of Silicon Retinas: Machine to machine communications for neuromorphic vision sensing data (IoSiRe))]. Published in: Proceedings of the Seventh InternationalConference on Image Processing Theory, Tools and Applications IPTA 2017. Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. ISSN (online) 2154-512X ISBN 9781538618417
Faculty, School or Research Centre:	Faculty of Science, Engineering and Computing Faculty of Science, Engineering and Computing > School of Computer Science and Mathematics
Date Deposited:	17 Dec 2020 13:11
Last Modified:	29 Sep 2022 10:35
DOI:	https://doi.org/10.1109/ICASSP40776.2020.9054303
URI:	https://eprints.kingston.ac.uk/id/eprint/47312

Actions (Repository Editors)

Item Control Page