Fast facial landmark detection and applications: a survey

Dense facial landmark detection is one of the key elements of face processing pipeline. It is used in virtual face reenactment, emotion recognition, driver status tracking, etc. Early approaches were suitable for facial landmark detection in controlled environments only, which is clearly insufficien...

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Autores principales: Khabarlak, Kostiantyn, Koriashkina, Larysa
Formato: Articulo
Lenguaje:Inglés
Publicado: 2022
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/136225
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id I19-R120-10915-136225
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Computer vision
Edge computing
Facial landmarks
Neural networks
Mobile applications
Literature overview
Visión por computadora
Computación en la frontera
Puntos faciales de referencia
Redes neuronales artificiales
Aplicaciones Móviles
Estudio de la bibliografía
spellingShingle Ciencias Informáticas
Computer vision
Edge computing
Facial landmarks
Neural networks
Mobile applications
Literature overview
Visión por computadora
Computación en la frontera
Puntos faciales de referencia
Redes neuronales artificiales
Aplicaciones Móviles
Estudio de la bibliografía
Khabarlak, Kostiantyn
Koriashkina, Larysa
Fast facial landmark detection and applications: a survey
topic_facet Ciencias Informáticas
Computer vision
Edge computing
Facial landmarks
Neural networks
Mobile applications
Literature overview
Visión por computadora
Computación en la frontera
Puntos faciales de referencia
Redes neuronales artificiales
Aplicaciones Móviles
Estudio de la bibliografía
description Dense facial landmark detection is one of the key elements of face processing pipeline. It is used in virtual face reenactment, emotion recognition, driver status tracking, etc. Early approaches were suitable for facial landmark detection in controlled environments only, which is clearly insufficient. Neural networks have shown an astonishing qualitative improvement for in-the-wild face landmark detection problem, and are now being studied by many researchers in the field. Numerous bright ideas are proposed, often complimentary to each other. However, exploration of the whole volume of novel approaches is quite challenging. Therefore, we present this survey, where we summarize state-of-the-art algorithms into categories, provide a comparison of recently introduced in-the-wild datasets (e.g., 300W, AFLW, COFW, WFLW) that contain images with large pose, face occlusion, taken in unconstrained conditions. In addition to quality, applications require fast inference, and preferably on mobile devices. Hence, we include information about algorithm inference speed both on desktop and mobile hardware, which is rarely studied. Importantly, we highlight problems of algorithms, their applications, vulnerabilities, and briefly touch on established methods. We hope that the reader will find many novel ideas, will see how the algorithms are used in applications, which will enable further research.
format Articulo
Articulo
author Khabarlak, Kostiantyn
Koriashkina, Larysa
author_facet Khabarlak, Kostiantyn
Koriashkina, Larysa
author_sort Khabarlak, Kostiantyn
title Fast facial landmark detection and applications: a survey
title_short Fast facial landmark detection and applications: a survey
title_full Fast facial landmark detection and applications: a survey
title_fullStr Fast facial landmark detection and applications: a survey
title_full_unstemmed Fast facial landmark detection and applications: a survey
title_sort fast facial landmark detection and applications: a survey
publishDate 2022
url http://sedici.unlp.edu.ar/handle/10915/136225
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