Spatio-angular resolution trade-off in face recognition

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dc.contributor.authorAlam, Muhammad Zeshan
dc.contributor.authorKelowani, Sousso
dc.contributor.authorElsaeidy, Mohamed
dc.date.accessioned2024-06-10T06:25:39Z
dc.date.available2024-06-10T06:25:39Z
dc.date.issued2024
dc.departmentİstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractEnsuring robustness in face recognition systems across various challenging conditions is crucial for their versatility. State-of-the-art methods often incorporate additional information, such as depth, thermal, or angular data, to enhance performance. However, light field-based face recognition approaches that leverage angular information face computational limitations. This paper investigates the fundamental trade-off between spatio-angular resolution in light field representation to achieve improved face recognition performance. By utilizing macro-pixels with varying angular resolutions while maintaining the overall image size, we aim to quantify the impact of angular information at the expense of spatial resolution, while considering computational constraints. Our experimental results demonstrate a notable performance improvement in face recognition systems by increasing the angular resolution, up to a certain extent, at the cost of spatial resolution.
dc.identifier.citationAlam, M. Z., Kelowani, S. ve Elsaeidy, M. (2024). Spatio-angular resolution trade-off in face recognition. International Conference on Emerging Trends and Applications in Artificial Intelligence, ICETAI 2023 içinde 960, (358-369. ss.). İstanbul, September 8-9, 2023. http://dx.doi.org/10.1007/978-3-031-56728-5_30
dc.identifier.doi10.1007/978-3-031-56728-5_30
dc.identifier.endpage369
dc.identifier.isbn9783031567278
dc.identifier.issn2367-3370
dc.identifier.scopus2-s2.0-85193607656
dc.identifier.scopusqualityQ4
dc.identifier.startpage358
dc.identifier.urihttp://dx.doi.org/10.1007/978-3-031-56728-5_30
dc.identifier.urihttps://hdl.handle.net/20.500.12511/12598
dc.identifier.volume960
dc.indekslendigikaynakScopus
dc.institutionauthorElsaeidy, Mohamed
dc.language.isoen
dc.relation.ispartofInternational Conference on Emerging Trends and Applications in Artificial Intelligence, ICETAI 2023en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectConvolution Neural Networks
dc.subjectDeep Learning
dc.subjectFace Recognition
dc.subjectLight Field Imaging
dc.subjectSpatio-Angular Resolution
dc.titleSpatio-angular resolution trade-off in face recognition
dc.typeConference Object

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