Motion Detection Using Spiking Neural Network Model

Qingxiang Wu, TM McGinnity, LP Maguire, Jianyong Cai, German Valderrama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)
19 Downloads (Pure)

Abstract

Inspired by the behaviour of the human visual system, a spiking neural network is proposed to detect moving objects in a visual image sequence. The structure and the properties of the network are detailed in this paper. Simulation results show that the network is able to perform motion detection for dynamic visual image sequence. Boundaries of moving objects are extracted by the spiking neural network. Using the boundary, a moving object filter is created to take the moving objects from the grey image. The moving object images can be used to recognise moving objects. The moving tracks can be recorded for further analysis of behaviours of moving objects. It is promising to apply this approach to video processing domain and robotic visual systems.
Original languageEnglish
Title of host publicationUnknown Host Publication
Place of PublicationLNAI: Lecture Notes In Artificial Intelligence
PublisherSpringer
Pages76-83
Number of pages8
ISBN (Print)978-3-540-85983-3
DOIs
Publication statusPublished - 18 Sep 2008
EventICIC '08 Proceedings of the 4th international conference on Intelligent Computing - with Aspects of Artificial Intelligence - Shanghai, China
Duration: 18 Sep 2008 → …

Conference

ConferenceICIC '08 Proceedings of the 4th international conference on Intelligent Computing - with Aspects of Artificial Intelligence
Period18/09/08 → …

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Wu, Q., McGinnity, TM., Maguire, LP., Cai, J., & Valderrama, G. (2008). Motion Detection Using Spiking Neural Network Model. In Unknown Host Publication (pp. 76-83). LNAI: Lecture Notes In Artificial Intelligence: Springer. https://doi.org/10.1007/978-3-540-85984-0_10