@inproceedings{a3d62bd963e04bbcb3b6e83739f82036,
title = "Benchmarking photon-limited performance of optic flow processing algorithms",
abstract = "In this paper we present a simulation framework for testing and benchmarking the photon-limited performance of optic flow processing techniques. We explore the performance of traditional gradient-based and feature-based optic flow algorithms as well as the biologically-inspired elementary motion detector. We show that biologically-inspired spatial pooling techniques can successfully be implemented in the gradient-based image interpolation algorithm and the elementary motion detector to extend low-light capabilities by more than one order of magnitude. We also show that block matching algorithms can accurately compute optic flow even when a single frame may capture <1000 photons. This framework provides a tool to further explore the mechanisms that underlie the observed low-light performance of biological vision systems and to understand the relative performance of different approaches for implementing optic flow in hardware.",
keywords = "low-light vision, motion detection, optic flow",
author = "Andrew Berkovich and Geoffrey Barrows and Pamela Abshire",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Symposium on Circuits and Systems, ISCAS 2016 ; Conference date: 22-05-2016 Through 25-05-2016",
year = "2016",
month = jul,
day = "29",
doi = "10.1109/ISCAS.2016.7538910",
language = "English",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1766--1769",
booktitle = "ISCAS 2016 - IEEE International Symposium on Circuits and Systems",
}