0000000000765462

AUTHOR

Victor Asavei

0000-0002-4776-2542

showing 2 related works from this author

A Comprehensive Survey of Indoor Localization Methods Based on Computer Vision

2020

Computer vision based indoor localization methods use either an infrastructure of static cameras to track mobile entities (e.g., people, robots) or cameras attached to the mobile entities. Methods in the first category employ object tracking, while the others map images from mobile cameras with images acquired during a configuration stage or extracted from 3D reconstructed models of the space. This paper offers an overview of the computer vision based indoor localization domain, presenting application areas, commercial tools, existing benchmarks, and other reviews. It provides a survey of indoor localization research solutions, proposing a new classification based on the configuration stage…

0209 industrial biotechnologyQR codesComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologylcsh:Chemical technologyBiochemistryArticlecomputer visionAnalytical ChemistryDomain (software engineering)fiducial markers020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringComputer visionlcsh:TP1-11853D reconstructionElectrical and Electronic EngineeringInstrumentationOrientation (computer vision)business.industry3D reconstructionAtomic and Molecular Physics and Opticsindoor localizationVideo trackingRobot020201 artificial intelligence & image processingAugmented realityArtificial intelligencebusinessSensors
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Evaluation of the ARCore Indoor Localization Technology

2020

Augmented reality has become a very powerful tool nowadays. With the recent technological advance, smartphones have the ability to display augmented content on the screen. What makes the difference is the naturalness with which the multimedia content is superimposed over the video stream acquired with the phone's camera. This perfect overlay depends on the accurate estimation of the position and orientation of the smartphone's camera relative to the 3D representation of the space. ARCore is an augmented reality framework that computes the position and orientation of the smartphone. In order to assess the possibility of integrating ARCore within a virtual and augmented reality platform, we e…

Data visualizationNaturalnessbusiness.industryOrientation (computer vision)PhoneHuman–computer interactionComputer scienceAugmented realityOverlaybusinessRepresentation (mathematics)Visualization2020 19th RoEduNet Conference: Networking in Education and Research (RoEduNet)
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