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Artificial Intelligence Review

Erschienen in:

04.08.2018

Face detection techniques: a review

verfasst von: Ashu Kumar, Amandeep Kaur, Munish Kumar

Erschienen in: Artificial Intelligence Review | Ausgabe 2/2019

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Abstract

With the marvelous increase in video and image database there is an incredible need of automatic understanding and examination of information by the intelligent systems as manually it is getting to be plainly distant. Face plays a major role in social intercourse for conveying identity and feelings of a person. Human beings have not tremendous ability to identify different faces than machines. So, automatic face detection system plays an important role in face recognition, facial expression recognition, head-pose estimation, human–computer interaction etc. Face detection is a computer technology that determines the location and size of a human face in a digital image. Face detection has been a standout amongst topics in the computer vision literature. This paper presents a comprehensive survey of various techniques explored for face detection in digital images. Different challenges and applications of face detection are also presented in this paper. At the end, different standard databases for face detection are also given with their features. Furthermore, we organize special discussions on the practical aspects towards the development of a robust face detection system and conclude this paper with several promising directions for future research.

Vorheriger Artikel Scene analysis and search using local features and support vector machine for effective content-based image retrieval

Nächster Artikel A survey on techniques to handle face recognition challenges: occlusion, single sample per subject and expression

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Titel: Face detection techniques: a review
verfasst von: Ashu Kumar
Amandeep Kaur
Munish Kumar
Publikationsdatum: 04.08.2018
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 2/2019
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-018-9650-2

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