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A device-free locator using computer vision techniques

Dissertation (MSc (Computer Science))--University of Pretoria, 2007.

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Other Authors: Lalioti, Vali
Format: Thesis
Published: University of Pretoria 2013
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access_status_str Open Access
author2 Lalioti, Vali
author_browse Lalioti, Vali
author_facet Lalioti, Vali
collection Thesis
dc_rights_str_mv © 1999, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Dissertation (MSc (Computer Science))--University of Pretoria, 2007.
format Thesis
id oai:repository.up.ac.za:2263/29606
institution University of Pretoria (South Africa)
last_indexed 2026-06-10T12:39:56.368Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2013
publishDateRange 2013
publishDateSort 2013
publisher University of Pretoria
publisherStr University of Pretoria
record_format dspace
source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/29606 A device-free locator using computer vision techniques Lalioti, Vali upetd@up.ac.za Du Pisanie, L. Van den Bergh, Frans Human-computer interaction Computer vision Real time data processing UCTD Dissertation (MSc (Computer Science))--University of Pretoria, 2007. Device-free locators allow the user to interact with a system without the burden of being physically in contact with some input device or without being connected to the system with cables. This thesis presents a device-free locator that uses computer vision techniques to recognize and track the user's hand. The system described herein uses a video camera to capture live video images of the user, which are segmented and processed to extract features that can be used to locate the user's hand within the image. Two types of features, namely moment based invariants and Fourier descriptors, are compared experimentally. An important property of both these techniques is that they allow the recognition of hand-shapes regardless of affine transformation, e.g. rotation within the plane or scale changes. A neural network is used to classify the extracted features as belonging to one of several hand signals, which can be used in the locator system as 'button clicks' or mode indicators. The Siltrack system described herein illustrates that the above techniques can be implemented in real-time on standard hardware. Computer Science unrestricted 2013-09-07T16:06:21Z 2006-11-20 2013-09-07T16:06:21Z 1999-12-01 2007-11-20 2006-11-20 Dissertation Van den Bergh, F 1999, A device-free locator using computer vision techniques, MSc dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://hdl.handle.net/2263/29606 > H677/ag http://hdl.handle.net/2263/29606 http://upetd.up.ac.za/thesis/available/etd-11202006-101829/ © 1999, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria
spellingShingle Human-computer interaction
Computer vision
Real time data processing
UCTD
A device-free locator using computer vision techniques
title A device-free locator using computer vision techniques
title_full A device-free locator using computer vision techniques
title_fullStr A device-free locator using computer vision techniques
title_full_unstemmed A device-free locator using computer vision techniques
title_short A device-free locator using computer vision techniques
title_sort device free locator using computer vision techniques
topic Human-computer interaction
Computer vision
Real time data processing
UCTD
url http://hdl.handle.net/2263/29606
http://upetd.up.ac.za/thesis/available/etd-11202006-101829/