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[{"key": "dc.contributor.advisor", "value": "Jokinen, Kimmo", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.advisor", "value": "Miettinen, Arttu", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Kapanen, Sakari", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2018-05-07T17:45:18Z", "language": "", "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2018-05-07T17:45:18Z", "language": "", "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2018", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.other", "value": "oai:jykdok.linneanet.fi:1870045", "language": "", "element": "identifier", "qualifier": "other", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/57875", "language": "", "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Virtuaalitodellisuussilmikoiden p\u00e4\u00e4nseurantaj\u00e4rjestelm\u00e4n suorituskyvyn mittaamista varten kehitettiin mittausmenetelm\u00e4 ja sulautettu kameramoduuli. Kyse on p\u00e4\u00e4st\u00e4 p\u00e4\u00e4h\u00e4n mittauksesta (engl. end-to-end measurement), jossa robotti liikuttaa silmikkoa ja kamera mittaa sis\u00e4ll\u00f6n muutoksia n\u00e4yt\u00f6ll\u00e4. Tavoitteena on optisesti mitata p\u00e4\u00e4nseurantaj\u00e4rjestelm\u00e4n tarkkuutta kuvaamalla n\u00e4yt\u00f6n sis\u00e4lt\u00f6\u00e4 n\u00e4yt\u00f6n virkistykseen tahdistettuna. Ty\u00f6ss\u00e4 keskityttiin kameramoduulin ja siihen liittyvien konen\u00e4k\u00f6algoritmien kehitt\u00e4miseen.\r\n\r\nMittauksessa n\u00e4yt\u00f6ll\u00e4 on kolmiulotteinen kohde, jossa on tunnistettavia pisteit\u00e4. Paikallistamalla n\u00e4m\u00e4 pisteet kuvassa voidaan m\u00e4\u00e4ritt\u00e4\u00e4 grafiikkamoottorin virtuaalisen kameran asento (siirtym\u00e4 ja kiertym\u00e4) ja saada siten selville p\u00e4\u00e4nseurantaj\u00e4rjestelm\u00e4n arvioima asento. Mittaamalla t\u00e4t\u00e4 asentoa erilaisten robotilla toistettavien liikkeiden aikana saadaan tietoa seurannan ep\u00e4tarkkuuksista kuten ajautumisesta ja t\u00e4rin\u00e4st\u00e4.\r\n\r\nAsennon arvioimiseksi kehitettiin lineaariseen pienimm\u00e4n neli\u00f6summan sovitukseen perustuva menetelm\u00e4 pienten asennon muutosten mittaamiseksi. T\u00e4t\u00e4 menetelm\u00e4\u00e4 karakterisoitiin kertaamalla sit\u00e4 OpenCV-konen\u00e4k\u00f6kirjaston ep\u00e4lineaariseen vastaavaan menetelm\u00e4\u00e4n. Karakterisointi tehtiin Monte Carlo simulaatioilla, joissa simuloituun mittausdataan lis\u00e4ttiin kohinaa. Simulaatioissa huomattiin, ett\u00e4 tasomaisella kohdekuviolla asennon eri komponentit sekoittuvat kesken\u00e4\u00e4n. Lis\u00e4\u00e4m\u00e4ll\u00e4 malliin tason ulkopuoleinen piste saatiin ongelmanasettelua parannettua ja kohinaherkkyytt\u00e4 pienennetty\u00e4. Menetelm\u00e4lle johdettiin my\u00f6s virhe-estimaattori. Simulaatioiden lis\u00e4ksi tehtiin mittauksia robotilla ja HTC Vive -silmikolla.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "A measurement method and an embedded camera module were developed for measuring the performance of the tracking system of virtual reality headsets. The measurement setup is an end-to-end one where a robot moves the headset and the camera measures the changes of the display content. The objective is to optically measure the accuracy of the headset\u2019s tracking system by imaging the content on the device\u2019s display, synchronized to the display refresh. The thesis work focused on the development of the smart camera and the related computer vision algorithms.\r\n\r\nIn the measurement, a three-dimensional target object with detectable points is shown on display. By locating these points in the projected image, the pose (translation and rotation) of the virtual camera can be estimated. From this pose, one can deduce the head pose that is estimated by the headset\u2019s tracking system. By measuring the pose during different motion sequences performed by the robot, one can probe the tracking system for inaccuracies such as drifting and jitter.\r\n\r\nA simple pose estimation method based on linear least squares fitting was developed for measuring small pose changes. The method was characterized by Monte Carlo simulation against a non-linear pose estimation method implemented in the OpenCV computer vision library, with noise added to the source data to represent real measurement conditions. It was found that a planar target object caused ambiguities between the pose variables. In the simulations, adding an off-plane point to the target made the problem better conditioned and less sensitive to noise. Error estimates were derived for the new method. In addition to simulations, measurements with the robot and the HTC Vive headset were also performed.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted using Plone Publishing form by Sakari Kapanen (samakapa) on 2018-05-07 17:45:17.284526. Form: Pro gradu -lomake (https://kirjasto.jyu.fi/julkaisut/julkaisulomakkeet/pro-gradu-lomake). JyX data: [jyx_publishing-allowed (fi) =True]", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by jyx lomake-julkaisija (jyx-julkaisija.group@korppi.jyu.fi) on 2018-05-07T17:45:18Z\r\nNo. of bitstreams: 2\r\nURN:NBN:fi:jyu-201805072491.pdf: 4833941 bytes, checksum: 12be309a7dba4e8a85d31d639bf9e845 (MD5)\r\nlicense.html: 4815 bytes, checksum: 948083497e552aa4e21977589f042125 (MD5)", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2018-05-07T17:45:18Z (GMT). No. of bitstreams: 2\r\nURN:NBN:fi:jyu-201805072491.pdf: 4833941 bytes, checksum: 12be309a7dba4e8a85d31d639bf9e845 (MD5)\r\nlicense.html: 4815 bytes, checksum: 948083497e552aa4e21977589f042125 (MD5)\r\n Previous issue date: 2018", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "1 verkkoaineisto (90 sivua)", "language": "", "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.format.mimetype", "value": "application/pdf", "language": null, "element": "format", "qualifier": "mimetype", "schema": "dc"}, {"key": "dc.language.iso", "value": "eng", "language": "", "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.subject.other", "value": "virtuaalitodellisuus", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "konen\u00e4k\u00f6", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "asennon arviointi", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "testausautomaatio", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "virtual reality", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "computer vision", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "pose estimation", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "test automation", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "Optical measurement of virtual reality headset performance", "language": "", "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-201805072491", "language": "", "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Pro gradu -tutkielma", "language": "fi", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Master\u2019s thesis", "language": "en", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Matemaattis-luonnontieteellinen tiedekunta", "language": "fi", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Faculty of Sciences", "language": "en", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Fysiikan laitos", "language": "fi", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Department of Physics", "language": "en", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Fysiikka", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Physics", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.date.updated", "value": "2018-05-07T17:45:18Z", "language": "", "element": "date", 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