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Pregled bibliografske jedinice broj: 1078819

Regression-based methods for face alignment: A survey


Gogić, Ivan; Ahlberg, Jörgen; Pandžić, Igor S.
Regression-based methods for face alignment: A survey // Signal Processing, 178 (2021), 107755, 20 doi:10.1016/j.sigpro.2020.107755 (međunarodna recenzija, pregledni rad, znanstveni)


CROSBI ID: 1078819 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Regression-based methods for face alignment: A survey

Autori
Gogić, Ivan ; Ahlberg, Jörgen ; Pandžić, Igor S.

Izvornik
Signal Processing (0165-1684) 178 (2021); 107755, 20

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, pregledni rad, znanstveni

Ključne riječi
Face alignment ; Facial feature localization ; Facial landmarks detection ; Survey Regression

Sažetak
Face alignment is the process of determining a face shape given its location and size in an image. It is used as a basis for other facial analysis tasks and for human-machine interaction and augmented reality applications. It is a challenging problem due to the extremely high variability in facial appearance affected by many external (illumination, occlusion, head pose) and internal factors (race, facial expression). However, advances in deep learning combined with domain-related knowledge from previous research recently demonstrated impressive results nearly saturating the unconstrained benchmark data sets. The focus is shifting towards reducing the computational burden of the face alignment models since real-time performance is required for such a highly dynamic task. Furthermore, many applications target devices on the edge with limited computational power which puts even greater emphasis on computational efficiency. We present the latest development in regression-based approaches that have led towards nearly solving the face alignment problem in an unconstrained scenario. Various regression architectures are systematically explored and recent training techniques discussed in the context of face alignment. Finally, a benchmark comparison of the most successful methods is presented, taking into account execution time as well, to provide a comprehensive overview of this dynamic research field.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Igor Sunday Pandžić (autor)

Avatar Url Ivan Gogić (autor)

Citiraj ovu publikaciju

Gogić, Ivan; Ahlberg, Jörgen; Pandžić, Igor S.
Regression-based methods for face alignment: A survey // Signal Processing, 178 (2021), 107755, 20 doi:10.1016/j.sigpro.2020.107755 (međunarodna recenzija, pregledni rad, znanstveni)
Gogić, I., Ahlberg, J. & Pandžić, I. (2021) Regression-based methods for face alignment: A survey. Signal Processing, 178, 107755, 20 doi:10.1016/j.sigpro.2020.107755.
@article{article, year = {2021}, pages = {20}, DOI = {10.1016/j.sigpro.2020.107755}, chapter = {107755}, keywords = {Face alignment, Facial feature localization, Facial landmarks detection, Survey Regression}, journal = {Signal Processing}, doi = {10.1016/j.sigpro.2020.107755}, volume = {178}, issn = {0165-1684}, title = {Regression-based methods for face alignment: A survey}, keyword = {Face alignment, Facial feature localization, Facial landmarks detection, Survey Regression}, chapternumber = {107755} }
@article{article, year = {2021}, pages = {20}, DOI = {10.1016/j.sigpro.2020.107755}, chapter = {107755}, keywords = {Face alignment, Facial feature localization, Facial landmarks detection, Survey Regression}, journal = {Signal Processing}, doi = {10.1016/j.sigpro.2020.107755}, volume = {178}, issn = {0165-1684}, title = {Regression-based methods for face alignment: A survey}, keyword = {Face alignment, Facial feature localization, Facial landmarks detection, Survey Regression}, chapternumber = {107755} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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