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Titolo:
Face detection: A survey
Autore:
Hjelmas, E; Low, BK;
Indirizzi:
Univ Oslo, Dept Informat, N-0316 Oslo, Norway Univ Oslo Oslo Norway N-0316 iv Oslo, Dept Informat, N-0316 Oslo, Norway Univ Edinburgh, JCMB, Dept Meteorol, Edinburgh EH9 3JZ, Midlothian, Scotland Univ Edinburgh Edinburgh Midlothian Scotland EH9 3JZ Midlothian, Scotland
Titolo Testata:
COMPUTER VISION AND IMAGE UNDERSTANDING
fascicolo: 3, volume: 83, anno: 2001,
pagine: 236 - 274
SICI:
1077-3142(200109)83:3<236:FDAS>2.0.ZU;2-7
Fonte:
ISI
Lingua:
ENG
Soggetto:
FACIAL FEATURE-EXTRACTION; EYE-FEATURE-EXTRACTION; REAL-TIME FACE; NEURAL-NETWORK; DEFORMABLE TEMPLATES; HEAD TRACKING; COLOR IMAGES; RECOGNITION; ALGORITHM; SYSTEM;
Keywords:
face detection; face localization; facial feature detection; feature-based approaches; image-based approaches;
Tipo documento:
Review
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
202
Recensione:
Indirizzi per estratti:
Indirizzo: Hjelmas, E Univ Oslo, Dept Informat, POB 1080 Blindern, N-0316 Oslo, Norway Univ Oslo POB 1080 Blindern Oslo Norway N-0316 16 Oslo, Norway
Citazione:
E. Hjelmas e B.K. Low, "Face detection: A survey", COMP VIS IM, 83(3), 2001, pp. 236-274

Abstract

In this paper we present a comprehensive and critical survey of face detection algorithms. Face detection is a necessary first-step in face recognition systems, with the purpose of localizing and extracting the face region from the background. It also has several applications in areas such as content-based image retrieval, video coding, video conferencing, crowd surveillance, and intelligent human-computer interfaces. However, it was not until recently that the face detection problem received considerable attention among researchers. The human face is a dynamic object and has a high degree ofvariability in its apperance, which makes face detection a difficult problem in computer vision. A wide variety of techniques have been proposed, ranging from simple edge-based algorithms to composite high-level approaches utilizing advanced pattern recognition methods. The algorithms presented in this paper are classified as either feature-based or image-based and are discussed in terms of their technical approach and performance. Due to the lack of standardized tests, we do not provide a comprehensive comparative evaluation, but in cases where results are reported on common datasets, comparisons are presented. We also give a presentation of some proposed applications and possible application areas. (C) 2001 Academic Press.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 02/04/20 alle ore 19:26:31