A1 Journal article – refereed
Complexity Analysis of Iterative Basis Transformations Applied to Event-Based Signals




List of Authors: Ieng SH, Lehtonen E, Benosman R
Publisher: FRONTIERS MEDIA SA
Publication year: 2018
Journal name in source: FRONTIERS IN NEUROSCIENCE
Journal acronym: FRONT NEUROSCI-SWITZ
Volume number: 12
ISSN: 1662-453X

Abstract
This paper introduces an event-based methodology to perform arbitrary linear basis transformations that encompass a broad range of practically important signal transforms, such as the discrete Fourier transform (DFT) and the discrete wavelet transform (DWT). We present a complexity analysis of the proposed method, and show that the amount of required multiply-and-accumulate operations is reduced in comparison to frame-based method in natural video sequences, when the required temporal resolution is high enough. Experimental results on natural video sequences acquired by the asynchronous time-based neuromorphic image sensor (ATIS) are provided to support the feasibility of the method, and to illustrate the gain in computation resources.


Internal Authors/Editors

Downloadable publication

This is an electronic reprint of the original article.
This reprint may differ from the original in pagination and typographic detail. Please cite the original version.




Last updated on 2019-29-01 at 16:19