Building Face Detection with Face Divine Proportions

被引:3
|
作者
Oualla, Mohamed [1 ]
Ounachad, Khalid [2 ]
Sadiq, Abdelalim [3 ]
机构
[1] Moulay Ismail Univ, Errachidia, Morocco
[2] Ibn Toufail Univ, Dept Comp Sci, Fac Sci, Kenitra, Morocco
[3] Ibn Toufail Univ, Comp Sci, Dept Sci Fac, Kenitra, Morocco
关键词
Face detection; Haar-like features; Adaboost; Facial proportions; Golden ratio;
D O I
10.3991/ijoe.v17i04.19149
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, we proposed an algorithm for detecting multiple human faces in an image based on haar-like features to represent the invariant characteristics of a face. The choice of relevant and more representative features is based on the divine proportions of a face. This technique, widely used in the world of beauty, especially in aesthetic medicine, allows the face to be divided into a set of specific regions according to known mathematical measures. Then we used the Adaboost algorithm for the learning phase. All our work is based on the Viola and Jones algorithm, in particular their innovative technique called Integral Image, which calculates the value of a Haar-Like feature extracted from a face image. In the rest of this article, we will show that our approach is promising and can achieve high detection rates of up to 97%.
引用
收藏
页码:63 / 80
页数:18
相关论文
共 50 条
  • [31] Dominance Detection in Face-to-face Conversations
    Escalera, Sergio
    Martinez, Rosa M.
    Vitria, Jordi
    Radeva, Petia
    Teresa Anguera, M.
    2009 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPR WORKSHOPS 2009), VOLS 1 AND 2, 2009, : 856 - +
  • [32] Joint Face Detection and Initialization for Face Alignment
    Wang, Zhiwei
    Yang, Xin
    MULTIMEDIA MODELING (MMM 2017), PT I, 2017, 10132 : 164 - 175
  • [33] Occluded Face Detection, Face in Niqab Dataset
    Alashbi, Abdulaziz Ali Saleh
    Sunar, Mohd Shahrizal
    EMERGING TRENDS IN INTELLIGENT COMPUTING AND INFORMATICS: DATA SCIENCE, INTELLIGENT INFORMATION SYSTEMS AND SMART COMPUTING, 2020, 1073 : 209 - 215
  • [34] The extension of statistical face detection to face tracking
    Wu, HS
    Zelek, JS
    1ST CANADIAN CONFERENCE ON COMPUTER AND ROBOT VISION, PROCEEDINGS, 2004, : 10 - 17
  • [35] Generic face invariant model for face detection
    Taffar M.
    Benmohammed M.
    Advances in Intelligent and Soft Computing, 2011, 102 : 43 - 51
  • [36] Face detection dissociates from face identification
    Robertson, David J.
    Jenkins, Rob
    Burton, A. Mike
    VISUAL COGNITION, 2017, 25 (7-8) : 740 - 748
  • [37] What Is a Face? Critical Features for Face Detection
    Omer, Yael
    Sapir, Roni
    Hatuka, Yarin
    Yovel, Galit
    PERCEPTION, 2019, 48 (05) : 437 - 446
  • [38] Unconstrained Face Alignment without Face Detection
    Shao, Xiaohu
    Xing, Junliang
    Lv, Jiangjing
    Xiao, Chunlin
    Liu, Pengcheng
    Feng, Youji
    Cheng, Cheng
    2017 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW), 2017, : 2069 - 2077
  • [39] Efficient face candidates selector for face detection
    Wu, JX
    Zhou, ZH
    PATTERN RECOGNITION, 2003, 36 (05) : 1175 - 1186
  • [40] TEAMWORK THROUGH TEAM BUILDING: FACE-TO-FACE TO ONLINE
    Staggers, Julie
    Garcia, Susan
    Nagelhout, Ed
    BUSINESS AND PROFESSIONAL COMMUNICATION QUARTERLY, 2008, 71 (04) : 472 - 487