A Short Review of Methods for Face Detection and Multifractal Analysis

H. Ugail; V. Doherty; R. Zwiggelaar; S. Appleyard; G. Huddy; B. Rajoub; M. H. Yap

doi:10.1109/CW.2009.47

A Short Review of Methods for Face Detection and Multifractal Analysis

H. Ugail, V. Doherty, R. Zwiggelaar, S. Appleyard, G. Huddy, B. Rajoub, M. H. Yap

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (Non-Journal item)

10 Citations (Scopus)

236 Downloads (Pure)

Abstract

The purpose of this paper is to present short reviews the face detection techniques and to study the effect of Multifractal analysis in detecting facial features. In reviewing the existing techniques, we have compared the performance of Nilsson et al’s algorithm, Haar Training implemented within Open Source Computer Vision Library (OpenCV) and Keinzle’s algorithm in face detection. Then, we have produced some experimental results suggesting that the Multifractal approach would help to extract key facial features of a human face. We conclude the paper with some discussions on how the work can be taken further.

Original language	English
Title of host publication	International Conference on Cyberworlds, 7-11 September, University of Bradford, UK (2009).
Publisher	IEEE Press
Pages	7-11
Number of pages	5
ISBN (Electronic)	978-0-7695-3791-7
ISBN (Print)	978-0-7695-3791-7
DOIs	https://doi.org/10.1109/CW.2009.47
Publication status	Published - 13 Jun 2012

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title = "A Short Review of Methods for Face Detection and Multifractal Analysis",

abstract = "The purpose of this paper is to present short reviews the face detection techniques and to study the effect of Multifractal analysis in detecting facial features. In reviewing the existing techniques, we have compared the performance of Nilsson et al{\textquoteright}s algorithm, Haar Training implemented within Open Source Computer Vision Library (OpenCV) and Keinzle{\textquoteright}s algorithm in face detection. Then, we have produced some experimental results suggesting that the Multifractal approach would help to extract key facial features of a human face. We conclude the paper with some discussions on how the work can be taken further.",

author = "H. Ugail and V. Doherty and R. Zwiggelaar and S. Appleyard and G. Huddy and B. Rajoub and Yap, {M. H.}",

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AB - The purpose of this paper is to present short reviews the face detection techniques and to study the effect of Multifractal analysis in detecting facial features. In reviewing the existing techniques, we have compared the performance of Nilsson et al’s algorithm, Haar Training implemented within Open Source Computer Vision Library (OpenCV) and Keinzle’s algorithm in face detection. Then, we have produced some experimental results suggesting that the Multifractal approach would help to extract key facial features of a human face. We conclude the paper with some discussions on how the work can be taken further.

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A Short Review of Methods for Face Detection and Multifractal Analysis

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