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Vision on tap : an online computer vision toolkit

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dc.contributor.advisor Ramesh Raskar. en_US
dc.contributor.author Chiu, Kevin (Kevin Geeyoung) en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Architecture. Program in Media Arts and Sciences. en_US
dc.date.accessioned 2011-12-19T16:11:52Z
dc.date.available 2011-12-19T16:11:52Z
dc.date.copyright 2011 en_US
dc.date.issued 2011 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/67714
dc.description Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2011. en_US
dc.description This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. en_US
dc.description Cataloged from student submitted PDF version of thesis. en_US
dc.description Includes bibliographical references (p. 60-64). en_US
dc.description.abstract In this thesis, we present an online toolkit, based on a combination of a Scratch-based programming environment and computer vision libraries, manifested as blocks within the environment, integrated with a community platform for diffusing advances in computer vision to a general populace. We show that by providing these tools, non-developers are able to create and publish computer vision applications. The visual development environment includes a collection of algorithms that, despite being well known in the computer vision community, provide capabilities to commodity cameras that are not yet common knowledge. In support of this visual development environment, we also present an online community that allows users to share applications made in the environment, assisting the dissemination of both the knowledge of camera capabilities and advanced camera capabilities to users who have not yet been exposed to their existence or comfortable with their use. Initial evaluations consist of user studies that quantify the abilities afforded to the novice computer vision users by the toolkit, baselined against experienced computer vision users. en_US
dc.description.statementofresponsibility by Kevin Chiu. en_US
dc.format.extent 64 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Architecture. Program in Media Arts and Sciences. en_US
dc.title Vision on tap : an online computer vision toolkit en_US
dc.title.alternative Online computer vision toolkit en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Architecture. Program in Media Arts and Sciences. en_US
dc.identifier.oclc 766546372 en_US


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MIT-Mirage