dc.contributor.author | Kurpytė-Lipnickė, Dovilė | |
dc.contributor.author | Navakauskas, Dalius | |
dc.date.accessioned | 2023-09-18T20:02:40Z | |
dc.date.available | 2023-09-18T20:02:40Z | |
dc.date.issued | 2014 | |
dc.identifier.issn | 2255-9140 | |
dc.identifier.other | (BIS)VGT02-000028699 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/146109 | |
dc.description.abstract | The article reports on the investigation of augmented reality system which is designed for identification and augmentation of 100 different square markers. Marker recognition efficiency was investigated by rotating markers along x and y axis directions in range from −90° to 90°. Virtual simulations of four environments were developed: a) an intense source of light, b) an intense source of light falling from the left side, c) the non-intensive light source falling from the left side, d) equally falling shadows. The graphics were created using the OpenGL graphics computer hardware interface; image processing was programmed in C++ language using OpenCV, while augmented reality was developed in Java programming language using NyARToolKit. The obtained results demonstrate that augmented reality marker recognition algorithm is accurate and reliable in the case of changing lighting conditions and rotational angles – only 4 % markers were unidentified. Assessment of marker recognition efficiency let to propose marker classification strategy in order to use it for grouping various markers into distinct markers’ groups possessing similar recognition properties. | eng |
dc.format | PDF | |
dc.format.extent | p. 54-60 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Academic Search Complete | |
dc.relation.isreferencedby | DOAJ | |
dc.relation.isreferencedby | VINITI | |
dc.source.uri | https://ecce-journals.rtu.lv/article/view/553 | |
dc.subject | IK04 - Skaitmeninės signalų apdorojimo technologijos / Digital signal processing technologies | |
dc.title | An efficiency analysis of augmented reality marker recognition algorithm | |
dc.type | Straipsnis kitoje DB / Article in other DB | |
dcterms.references | 20 | |
dc.type.pubtype | S3 - Straipsnis kitoje DB / Article in other DB | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Elektronikos fakultetas / Faculty of Electronics | |
dc.subject.researchfield | N 009 - Informatika / Computer science | |
dc.subject.researchfield | T 001 - Elektros ir elektronikos inžinerija / Electrical and electronic engineering | |
dc.subject.ltspecializations | L106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies | |
dc.subject.en | Computers and information processing | |
dc.subject.en | Computational efficiency | |
dc.subject.en | Augmented reality | |
dc.subject.en | Image recognition | |
dc.subject.en | Open source software | |
dcterms.sourcetitle | Electrical, control and communication engineering | |
dc.description.volume | Vol. 5 | |
dc.publisher.name | Riga Technical University | |
dc.publisher.city | Riga | |
dc.identifier.doi | 10.2478/ecce-2014-0008 | |
dc.identifier.elaba | 4082959 | |