Real-Time Computing of Touch Topology via Poincare–Hopf Index

While visual or tactile image data have been conventionally processed via filters or perceptron-like learning machines, the recent advances of computational topology may make it possible to successfully extract the global features from the local pixelwise data. In fact, some inventive algorithms hav...

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Bibliographic Details
Main Authors: Keiji Miura, Kazuki Nakada
Format: Article
Language:English
Published: IEEE 2015-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/7339652/
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spelling doaj-2616f92ca166430e960d7f5d918bf80f2021-03-29T19:35:44ZengIEEEIEEE Access2169-35362015-01-0132566257110.1109/ACCESS.2015.25043877339652Real-Time Computing of Touch Topology via Poincare–Hopf IndexKeiji Miura0Kazuki Nakada1School of Science and Technology, Kwansei Gakuin University, Sanda, JapanGraduate School of Information Sciences, Hiroshima City University, Hiroshima, JapanWhile visual or tactile image data have been conventionally processed via filters or perceptron-like learning machines, the recent advances of computational topology may make it possible to successfully extract the global features from the local pixelwise data. In fact, some inventive algorithms have succeeded in computing the topological invariants, such as the number of objects or holes and irrespective of the shapes and positions of the touches. However, they are mostly offline algorithms aiming at big data. A real-time algorithm for computing topology is also needed for interactive applications such as touch sensors. Here, we propose a fast algorithm to compute the Euler characteristics of touch shapes by using the Poincare-Hopf index for each pixel. We demonstrate that our simple algorithm, implemented solely as logical operations in Arduino, correctly returns and updates the topological invariants of touches in real time.https://ieeexplore.ieee.org/document/7339652/Poincare-Hopf indextopologyinvariancetouch countersensor networks
collection DOAJ
language English
format Article
sources DOAJ
author Keiji Miura
Kazuki Nakada
spellingShingle Keiji Miura
Kazuki Nakada
Real-Time Computing of Touch Topology via Poincare–Hopf Index
IEEE Access
Poincare-Hopf index
topology
invariance
touch counter
sensor networks
author_facet Keiji Miura
Kazuki Nakada
author_sort Keiji Miura
title Real-Time Computing of Touch Topology via Poincare–Hopf Index
title_short Real-Time Computing of Touch Topology via Poincare–Hopf Index
title_full Real-Time Computing of Touch Topology via Poincare–Hopf Index
title_fullStr Real-Time Computing of Touch Topology via Poincare–Hopf Index
title_full_unstemmed Real-Time Computing of Touch Topology via Poincare–Hopf Index
title_sort real-time computing of touch topology via poincare–hopf index
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2015-01-01
description While visual or tactile image data have been conventionally processed via filters or perceptron-like learning machines, the recent advances of computational topology may make it possible to successfully extract the global features from the local pixelwise data. In fact, some inventive algorithms have succeeded in computing the topological invariants, such as the number of objects or holes and irrespective of the shapes and positions of the touches. However, they are mostly offline algorithms aiming at big data. A real-time algorithm for computing topology is also needed for interactive applications such as touch sensors. Here, we propose a fast algorithm to compute the Euler characteristics of touch shapes by using the Poincare-Hopf index for each pixel. We demonstrate that our simple algorithm, implemented solely as logical operations in Arduino, correctly returns and updates the topological invariants of touches in real time.
topic Poincare-Hopf index
topology
invariance
touch counter
sensor networks
url https://ieeexplore.ieee.org/document/7339652/
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AT kazukinakada realtimecomputingoftouchtopologyviapoincarex2013hopfindex
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