Please use this identifier to cite or link to this item: https://doi.org/10.1109/BioCAS.2013.6679700
DC FieldValue
dc.titleReal-time motion estimation using spatiotemporal filtering in FPGA
dc.contributor.authorOrchard, G.
dc.contributor.authorThakor, N.V.
dc.contributor.authorEtienne-Cummings, R.
dc.date.accessioned2016-10-19T08:45:01Z
dc.date.available2016-10-19T08:45:01Z
dc.date.issued2013
dc.identifier.citationOrchard, G.,Thakor, N.V.,Etienne-Cummings, R. (2013). Real-time motion estimation using spatiotemporal filtering in FPGA. 2013 IEEE Biomedical Circuits and Systems Conference, BioCAS 2013 : 306-309. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/BioCAS.2013.6679700" target="_blank">https://doi.org/10.1109/BioCAS.2013.6679700</a>
dc.identifier.isbn9781479914715
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/128774
dc.description.abstractReliable visual motion estimation is typically regarded as a difficult problem. Noise sensitivity and computational requirements often prohibit effective real-time application on mobile platforms. Despite these difficulties, biological systems reliably estimate visual motion in real-time and heavily rely on it. Here we present an FPGA implementation of a biologically inspired spatiotemporal energy model for motion estimation. The model realises 720 motion sensitive units per pixel for video of resolution 128×128 pixels at 30FPS, thus providing a computational tool for further investigation of spatiotemporal energy models. © 2013 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/BioCAS.2013.6679700
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentTEMASEK LABORATORIES
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.doi10.1109/BioCAS.2013.6679700
dc.description.sourcetitle2013 IEEE Biomedical Circuits and Systems Conference, BioCAS 2013
dc.description.page306-309
dc.identifier.isiutNOT_IN_WOS
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