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dc.contributor.authorPurnomo, Fendi Aji
dc.contributor.authorSantosa, P. Insap
dc.contributor.authorHartanto, Rudy
dc.date.accessioned2014-12-03T08:20:32Z
dc.date.available2014-12-03T08:20:32Z
dc.date.issued2014-12-04
dc.identifier.citation[1] Azuma, A. (1997), Survey of Augmented Reality, Presence: Teleoperators and Virtual Environments 6, 4, 355 – 385, 1997. [Online] Available : http://www.cs.unc.edu/~azuma/ARpresence.pdf [2] Liegsalz, F, Evaluation of The Impact of Super Resolution on Tracking Accuracy, Ottobrunn: tum.de, 2012. [Online] Available : https://campar.in.tum.de/twiki/pub/Students/MaSuperR esoultionOnTracking/a00460.pdf [3] Herakleous, K & Poullis, Cimproving Augmented Reality Applications With Optical Flow, IEEE 2013, 978-1-4799-2341-0 [4] Feng. Z, Henry, B.D, Mark, B. 2008 , Trends In Augmented Reality Tracking, Interaction And Display: A Review Of Ten Years Of ISMAR, Singapore : Nanyang Technology University, 2008. [5] Persa. S., Sensor Fusion in Head Pose Tracking for Augmented Reality, Wöhrmann Print Service, 2006. [Online] Available http://homepage.tudelft.nl/c7c8y/Theses/PhDThesisPer sa.pdf [6] Kato. H., Billinghurst, M. Poupyrev, I. Tetsutani, N. dan Tachibana, K., Tangible Augmented Reality, Nagoya, Japan : Proceedings of Nicograph, 2001. [7] R. Hartley and A. Zisserman, "Multiple View Geometry in Computer Vision," Cambridge University Press, pp. 155-157, 2003. [8] Geroimenko, V. (2012). Augmented Reality Technology and Art: The Analysis and Visualization of Evolving Conceptual Models. Information Visualisation (IV), 2012 16th International Conference (pp. 445-453). IEEE. [9] Siltanen, S. (2012). Theory and applications of marker-based augmented reality. Finland. [10] David G. Lowe, Object Recognition from Local ScaleInvariant Features, Computer Science Department, University of British Columbia, 2004. [11] Mohamed Aly, “Face Recognition using SIFT Features”, CNS186 Term Project, Winter 2006.en_US
dc.identifier.issn2407-4330
dc.identifier.urihttp://hdl.handle.net/11617/4993
dc.description.abstractThe most common problem in Augmented Reality (AR) is the inability of detecting marker in different angle to show the expected virtual object. This study has been conducted to improve the ability reading / tracking in order to overcome the inability of AR in marker tracking for different angle. The method is to find the angle of the tracking error with rotation. Based on found angle of each corner and then registering the target image to the same virtual object. The marker is a 3D real object (marker-less) which captured into movie to produce 3D objects with the same condition. The conversion of the target image into multi marker using Vuforia. Testing is conducted with angle tracking variation to the emergence of the virtual object. The result of this study stated that the reading ability can be done by the application of AR which is virtual object appear for tracking variations for angle between 0 and 360.en_US
dc.publisherUniversitas Muhammadiyah Surakartaen_US
dc.subjectmulti markeren_US
dc.subjecttracking improvementen_US
dc.subjectmarker angleen_US
dc.subjectaugmented realityen_US
dc.titleImproved Tracking Capabilities With Collaboration Multimarker Augmented Realityen_US
dc.typeArticleen_US


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