A multifactor comparative assessment of augmented reality frameworks in diverse computing settings

Simple item page
dc.contributor.authorManeli, Mfundo A.
dc.contributor.authorIsafiade, Omowunmi E.
dc.date.accessioned2023-02-28T08:09:08Z
dc.date.available2023-02-28T08:09:08Z
dc.date.issued2023
dc.description.abstractResearch and development on different augmented reality (AR) frameworks have come a long way when it comes to image tracking, object tracking, plane tracking and light estimation. However, there might be trade-offs and varying results obtained from different AR frameworks, depending on the use cases, and this is critical for consideration during immersive application development. Besides the current literature effort, this research proposes a multifactor comparative analysis of two core AR frameworks, which aims to analyze and evaluate ARKit and ARCore in diverse computing settings. This research developed a structural application which evaluated three major test parameters across ten devices spanning ARKit and ARCore. The first parameter relates to evaluating AR measurements using four different distance criteria. The second parameter evaluated resource utilization, relating to the central processing unit (CPU) and random access memory (RAM), while the last parameter evaluated plane detection based on light estimation.en_US
dc.identifier.citationManeli, M. A., & Isafiade, O. E. (2023). A multifactor comparative assessment of augmented reality frameworks in diverse computing settings. IEEE Access, 11, 12474 - 12486. 10.1109/ACCESS.2023.3242238en_US
dc.identifier.issn2169-3536
dc.identifier.uri10.1109/ACCESS.2023.3242238
dc.identifier.urihttp://hdl.handle.net/10566/8469
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.subjectComputer scienceen_US
dc.subjectOperating systemsen_US
dc.subjectInterneten_US
dc.subjectMobile computingen_US
dc.titleA multifactor comparative assessment of augmented reality frameworks in diverse computing settingsen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
maneli_a multifactor comparative assessment_2023.pdf
Size:
3.5 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Research Articles (Computer Science)