Skip to main content

Advertisement

SpringerLink
Log in

A review of facial gender recognition

  • Survey
  • Published:
Pattern Analysis and Applications Aims and scope Submit manuscript

Abstract

Applications such as human–computer interaction, surveillance, biometrics and intelligent marketing would benefit greatly from knowledge of the attributes of the human subjects under scrutiny. The gender of a person is one such significant demographic attribute. This paper provides a review of facial gender recognition in computer vision. It is certainly not a trivial task to identify gender from images of the face. We highlight the challenges involved, which can be divided into human factors and those introduced during the image capture process. A comprehensive survey of facial feature extraction methods for gender recognition studied in the past couple of decades is provided. We appraise the datasets used for evaluation of gender classification performance. Based on the results reported, good performance has been achieved for images captured under controlled environments, but certainly there is still much work that can be done to improve the robustness of gender recognition under real-life environments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Abdi H., Valentin D, Edelman B, O’Toole A (1995) More about the difference between men and women: evidence from linear neural networks and the principal-component approach. Perception 24(5):539–62 (1995)

  2. Aghajanian J, Warrell J, Prince SJD, Rohn JL, Baum B (2009) Patch-based within-object classification. In: 2009 IEEE 12th international conference on computer vision. IEEE, pp 1125–1132

  3. Ahmed A, Yu K, Xu W, Gong Y, Xing E (2008) Training hierarchical feed-forward visual recognition models using transfer learning from pseudo-tasks. In: Computer Vision-ECCV 2008, pp 69–82

  4. Alexandre LA (2012) Gender recognition: a multiscale decision fusion approach. Pattern Recognit Lett 31(11):1422–1427. doi:10.1016/j.patrec.2010.02.010

  5. Alomar FA, Muhammad G, Aboalsamh H, Hussain M, Mirza AM, Bebis G (2013) Gender recognition from faces using bandlet and local binary patterns. In: 2013 20th international conference on systems, signals and image processing (IWSSIP). IEEE, pp 59–62. doi:10.1109/IWSSIP.2013.6623449

  6. Anderson K, McOwan PW (2004) Robust real-time face tracker for cluttered environments. Comput Vis Image Underst 95(2):184–200. doi:10.1016/j.cviu.2004.01.001

  7. Andreu Y, García-Sevilla P, Mollineda RA (2014) Face gender classification: a statistical study when neutral and distorted faces are combined for training and testing purposes. Image Vis Comput 32(1):27–36. doi:10.1016/j.imavis.2013.11.001

  8. Andreu Y, Mollineda R, Garcia-Sevilla P (2009) Gender recognition from a partial view of the face using local feature vectors. In: Pattern recognition and image analysis, pp 481–488

  9. Ardakany AR, Nicolescu M, Nicolescu M (2013) An extended local binary pattern for gender classification. In: 2013 IEEE international symposium on multimedia. IEEE, pp 315–320. doi:10.1109/ISM.2013.61

  10. Ballihi L, Ben Amor B, Daoudi M, Srivastava A, Aboutajdine D (2012) Geometric based 3D facial gender classification. In: 2012 5th international symposium on communications, control and signal processing. IEEE, pp 1–5. doi:10.1109/ISCCSP.2012.6217828

  11. Baluja S, Rowley H (2007) Boosting sex identification performance. Int J Comput Vis 71(1):111–119

  12. BeFIT—Benchmarking Facial Image Analysis Technologies. http://fipa.cs.kit.edu/412.php. Accessed 12 Mar 2012

  13. Bekios-Calfa J, Buenaposada J, Baumela L (2011) Revisiting linear discriminant techniques in gender recognition. Pattern Anal Mach Intell IEEE Trans 33(4):858–864

  14. Bekios-Calfa J, Buenaposada JM, Baumela L (2014) Robust gender recognition by exploiting facial attributes dependencies. Pattern Recognit Lett 36:228–234. doi:10.1016/j.patrec.2013.04.028

  15. Benabdelkader C, Griffin P (2005) A local region-based approach to gender classification from face images. In: Computer vision and pattern recognition-workshops, 2005. CVPR Workshops. IEEE Computer Society Conference on, p 52

  16. Bruce V, Burton A, Hanna E, Healey P, Mason O, Coombes A, Fright R, Linney A (1993) Sex discrimination: how do we tell the difference between male and female faces? Perception 22(2):131–152

  17. Bruce V, Valentine T, Baddeley A (1987) The basis of the 3/4 view advantage in face recognition. Appl Cogn Psychol 1(2):109–120

  18. Brunelli R, Poggio T (1993) Face recognition: features versus templates. IEEE Trans Pattern Anal Mach Intell 15(10):1042–1052 (1993)

  19. Bucak S, Jin R, Jain A (2014) Multiple kernel learning for visual object recognition: a review. IEEE Trans Pattern Anal Mach Intell 36(7):1354–1369. doi:10.1109/TPAMI.2013.212

  20. Buchala S, Davey N, Frank R, Gale T, Loomes M, Kanargard W (2004) Gender classification of face images: the role of global and feature-based information. In: Neural information processing. Springer, Berlin, pp 763–768

  21. Buchala S, Davey N, Gale T (2005) Analysis of linear and nonlinear dimensionality reduction methods for gender classification of face images. Int J Syst Sci 36(14):931–942 (2005)

  22. Buchala S, Davey N, Gale T (2005) Principal component analysis of gender, ethnicity, age, and identity of face images. In: Proceedings of IEEE ICMI

  23. Buchala S, Loomes M, Davey N, Frank R (2005) The role of global and feature based information in gender classification of faces: a comparison of human performance and computational models. Int J Neural Syst 15:121–128

  24. Bui L, Tran D, Huang X, Chetty G (2010) Face gender recognition based on 2D principal component analysis and support vector machine. In: Network and system security (NSS), 2010 4th international conference on, pp 579–582. doi:10.1109/NSS.2010.19

  25. Caldwell T (2011) Vending machines recommend based on face recognition. Biom Technol Today 2011(1):12. doi:10.1016/S0969-4765(11)70018-2

    Article  MathSciNet  Google Scholar 

  26. Castrillón M, Déniz O, Hernández D, Dominguez A (2003) Identity and gender recognition using the ENCARA real-time face detector. In: Conferencia de la Asociacin Espaola para la Inteligencia Artificial., vol 3

  27. Castrillón-Santana M, Lorenzo-Navarro J, Ramon-Balmaseda E (2013) Improving gender classification accuracy in the wild. In: Progress in pattern recognition, image analysis, computer vision, and applications, pp 270–277. doi:10.1007/978-3-642-41827-3_34

  28. Castrillón-Santana M, Vuong Q (2007) An analysis of automatic gender classification. In: Progress in pattern recognition, image analysis and applications, vol 4756, pp 271–280

  29. Chen H, Gallagher A, Girod B (2012) Describing clothing by semantic attributes. In: Computer vision—ECCV 2012, pp 609–623

  30. Chen W, Lee P, Hsieh L (2013) Gender classification of face with moment descriptors. In: The Eighth international multi-conference on computing in the global information technology (ICCGI’13), pp 72–75

  31. Cootes T, Edwards G, Taylor C (2001) Active appearance models. IEEE Trans Pattern Anal Mach Intell 23(6):681–685. doi:10.1109/34.927467

  32. Dago-Casas P, Gonzalez-Jimenez D, Yu L, Alba-Castro J (2011) Single-and cross-database benchmarks for gender classification under unconstrained settings. In: Computer vision workshops (ICCV Workshops), 2011 IEEE international conference on, pp 2152–2159

  33. Demirkus M, Toews M, Clark J, Arbel T (2010) Gender classification from unconstrained video sequences. In: Computer vision and pattern recognition workshops (CVPRW), 2010 IEEE computer society conference on. IEEE, pp 55–62

  34. Fellous J (1997) Gender discrimination and prediction on the basis of facial metric information. Vis Res 37(14):1961–1973

  35. Flynn P, Bowyer K, Phillips P (2003) Assessment of time dependency in face recognition: An initial study. In: Audio-and video-based biometric person authentication. Springer, Berlin, p 1057

  36. Fu X, Dai G, Wang C, Zhang L (2010) Centralized Gabor gradient histogram for facial gender recognition. In: Natural computation (ICNC), 2010 sixth international conference on, vol 4. IEEE, pp 2070–2074

  37. Gallagher A, Chen T (2009) Understanding images of groups of people. In: 2009 IEEE conference on computer vision and pattern recognition. IEEE, pp 256–263. doi:10.1109/CVPR.2009.5206828

  38. Gao W, Ai H (2009) Face gender classification on consumer images in a multiethnic environment. Adv Biom 169–178

  39. Gao W, Cao B, Shan S, Chen X (2008) The CAS-PEAL large-scale Chinese face database and baseline evaluations. Syst Man Cybern Part A Syst Hum IEEE Trans 38(1):149–161

  40. Gehrig T, Steiner M, Ekenel HK (2011) Draft: evaluation guidelines for gender classification and age estimation. Tech. rep. http://fipa.cs.kit.edu/download/befit-evaluation_guidelines.pdf. Accessed 12 Mar 2012

  41. Gilani SZ, Shafait F, Mian A (2013) Biologically significant facial landmarks: how significant are they for gender classification? In: 2013 International conference on digital image computing: techniques and applications (DICTA), vol 1. IEEE, pp 1–8. doi:10.1109/DICTA.2013.6691488

  42. Golomb B, Lawrence D, Sejnowski T (1991) Sexnet: a neural network identifies sex from human faces. Adv Neural Inf Process Syst 3:572–577

  43. Graf AB, Wichmann FA (2002) Gender classification of human faces. Biol Moti Comput Vis 2525:491–500

  44. Guo G, Dyer C, Fu Y, Huang T (2009) Is gender recognition affected by age? In: Computer vision workshops (ICCV Workshops), 2009 IEEE 12th international conference on. IEEE, pp 2032–2039

  45. Gutta S, Huang J, Jonathon P (2000) Mixture of experts for classification of gender, ethnic origin, and pose of human faces. Neural Netw IEEE Trans 11(4):948–960

  46. Han X, Ugail H, Palmer I (2009) Gender classification based on 3D face geometry features using SVM. In: CyberWorlds, 2009 (CW’09). International conference on. IEEE, pp 114–118. doi:10.1109/CW.2009.41

  47. He X, Niyogi P (2004) Locality preserving projections. Neural Inf Process Syst 16:153

  48. Hillel A, Weinshall D (2007) Subordinate class recognition using relational object models. Adv Neural Inf Process Syst 19:73

  49. Hosoi S, Takikawa E, Kawade M (2004) Ethnicity estimation with facial images. In: Automatic face and gesture recognition, 2004. Proceedings. Sixth IEEE international conference on. IEEE, pp 195–200

  50. Hu Y, Yan J, Shi P (2010) A fusion-based method for 3d facial gender classification. In: Computer and automation engineering (ICCAE), 2010 The 2nd International Conference on, vol 5. IEEE, pp. 369–372

  51. Huang D, Ding H, Wang C, Wang Y, Zhang G, Chen L (2014) Local circular patterns for multi-modal facial gender and ethnicity classification. Image Vis Comput. doi:10.1016/j.imavis.2014.06.009

  52. Huang G, Mattar M, Berg T, Learned-Miller E (2008) Labeled faces in the wild: a database for studying face recognition in unconstrained environments. In: Workshop on faces in’Real-Life’Images: detection, alignment, and recognition

  53. Hussain M, Al-Otaibi S, Muhammad G (2013) Gender recognition using nonsubsampled contourlet transform and WLD descriptor. In: Image analysis, pp 373–383. doi:10.1007/978-3-642-38886-6_36

  54. Huynh T, Min R, Dugelay J (2013) An efficient LBP-based descriptor for facial depth images applied to gender recognition using RGB-D face data. In: Computer vision-ACCV 2012 workshops, pp 133–145. doi:10.1007/978-3-642-37410-4_12

  55. Jabid T, Hasanul Kabir M, Chae O (2010) Gender classification using local directional pattern (LDP). In: Pattern recognition (ICPR), 2010 20th International conference on. IEEE, pp 2162–2165 (2010). doi:10.1109/ICPR.2010.373

  56. Jain A, Huang J, Fang S (2005) Gender identification using frontal facial images. In: Multimedia and Expo, 2005. ICME 2005. IEEE international conference on, p 4

  57. Jain AK, Ross A, Prabhakar S (2004) An introduction to biometric recognition. IEEE Trans Circuits Syst 14(1):4–20

  58. Jesorsky O, Kirchberg K, Frischholz R (2001) Robust face detection using the Hausdorff distance. In: Bigun J, Smeraldi F (eds) Audio-and video-based biometric person authentication. Springer, Berlin, pp 90–95

  59. Khorsandi R, Abdel-Mottaleb M (2013) Gender classification using 2-D ear images and sparse representation. In: 2013 IEEE Workshop on applications of computer vision (WACV), pp 461–466. doi:10.1109/WACV.2013.6475055

  60. Khorsandi R, Abdel-mottaleb M (2013) Gender classification using facial images and basis pursuit. In: Computer analysis of images and patterns, pp 294–301

  61. Khoshkerdar E, Kanan HR (2013) Gender classification using GA-based adjusted order PZM and fuzzy similarity measure. In: 2013 13th Iranian conference on fuzzy systems (IFSC). IEEE, pp 1–4. doi:10.1109/IFSC.2013.6675684

  62. Lapedriza A, Marin-Jimenez M, Vitria J (2006) Gender recognition in non controlled environments. In: Pattern recognition, 2006. ICPR 2006. 18th International Conference on, vol 3, pp 834–837

  63. Lee JD, Lin CY, Huang CH (2013) Novel features selection for gender classification. In: 2013 IEEE international conference on mechatronics and automation. IEEE, pp 785–790

  64. Lee P, Hung J, Hung Y (2010) Automatic gender recognition using fusion of facial strips. In: Pattern recognition (ICPR), 2010 20th international conference on, pp 1140–1143

  65. Lee T (1996) Image representation using 2D Gabor wavelets. IEEE Trans Pattern Anal Mach Intell 18(10):959–971. doi:10.1109/34.541406

  66. Leng X, Wang Y (2008) Improving generalization for gender classification. In: Image processing, 2008. ICIP 2008. 15th IEEE international conference on. IEEE, pp 1656–1659

  67. Li B, Lian XC, Lu BL (2011) Gender classification by combining clothing, hair and facial component classifiers. Neurocomputing 1–10. doi:10.1016/j.neucom.2011.01.028

  68. Li M, Bao S, Dong W, Wang Y, Su Z (2013) Head-shoulder based gender recognition. In: ICIP, pp 2753–2756

  69. Li Z, Liu J, Tang J, Lu H (2015) Robust structured subspace learning for data pepresentation. IEEE Trans Pattern Anal Mach Intell X(X):1–1. doi:10.1109/TPAMI.2015.2400461

  70. Li Z, Zhou X (2009) Spatial gaussian mixture model for gender recognition. In: Image Processing (ICIP), 2009 16th, pp 45–48

  71. Lian H, Lu B (2006) Multi-view gender classification using local binary patterns and support vector machines. In: Advances in Neural Networks-ISNN 2006, pp. 202–209

  72. Lian H, Lu B, Takikawa E (2005) Gender recognition using a min-max modular support vector machine. In: Advances in Natural Computation, pp 433–436

  73. Liu F, Tang J, Song Y, Xiang X, Tang Z (2014) Local structure based sparse representation for face recognition with single sample per person. In: 2014 IEEE international conference on image processing (ICIP). IEEE, pp 713–717. doi:10.1109/ICIP.2014.7025143

  74. Lowe D (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91–110

  75. Lu H, Huang Y, Chen Y, Yang D (2008) Automatic gender recognition based on pixel-pattern-based texture feature. J Real Time Image Process 3(1):109–116. doi:10.1007/s11554-008-0072-2

  76. Lu L, Shi P (2009) A novel fusion-based method for expression-invariant gender classification. In: Acoustics, speech and signal processing, 2009. ICASSP 2009. IEEE international conference on, pp 1065–1068

  77. Lu L, Shi P (2009) Fusion of multiple facial regions for expression-invariant gender classification. IEICE Electron Express 6(10):587–593. doi:10.1587/elex.6.587

  78. Lu X, Chen H, Jain A (2005) Multimodal facial gender and ethnicity identification. In: Advances in Biometrics, pp 554–561

  79. Lyle JR, Miller PE, Pundlik SJ, Woodard DL (2012) Soft biometric classification using local appearance periocular region features. Pattern Recognit 45(11):3877–3885. doi:10.1016/j.patcog.2012.04.027

  80. Mairal J, Bach F, Ponce J (2012) Task-driven dictionary learning. IEEE Trans Pattern Anal Mach Intell 34(4):791–804. doi:10.1109/TPAMI.2011.156

  81. Mäkinen E, Raisamo R (2008) An experimental comparison of gender classification methods. Pattern Recognit Lett 29(10):1544–1556

  82. Makinen E, Raisamo R (2008) Evaluation of gender classification methods with automatically detected and aligned faces. Pattern Anal Mach Intell IEEE Trans 30(3):541–547

  83. Manesh FS, Ghahramani M, Tan YP (2010) Facial part displacement effect on template-based gender and ethnicity classification. In: 2010 11th international conference on control automation robotics & vision. IEEE, pp 1644–1649

  84. Martinez A, Benavante R (1998) The AR face database. Tech. rep. http://www.cat.uab.cat/Public/Publications/1998/MaB1998/CVCReport24.pdf. Accessed 18 Mar 2012

  85. Mayo M, Zhang E (2008) Improving face gender classification by adding deliberately misaligned faces to the training data. In: Image and vision computing New Zealand, 2008. IVCNZ 2008. 23rd International conference. IEEE, pp 1–5

  86. Messer K, Matas J, Kittler J, Luettin J, Maitre G (1999) XM2VTSdb: the extended M2VTS database. In: Proceedings 2nd conference on audio and video-base biometric personal verification (AVBPA99)

  87. Meyers E, Wolf L (2007) Using biologically inspired features for face processing. Int J Comput Vis 76(1):93–104. doi:10.1007/s11263-007-0058-8

  88. Mirza A, Hussain M (2013) Gender recognition using fusion of local and global facial features. In: Advances in Visual Computing, pp 493–502

  89. Moeini A, Moeini H (2015) Pose-invariant gender classification based on 3D face reconstruction and synthesis from single 2D image. Electron Lett 51(10):760–762. doi:10.1049/el.2015.0520

  90. Moghaddam B, Yang M (2002) Learning gender with support faces. Pattern Anal Mach Intell IEEE Trans 24(5):707–711

  91. Mozaffari S, Behravan H, Akbari R (2010) Gender classification using single frontal image per person: combination of appearance and geometric based features. In: 2010 20th international conference on pattern recognition. IEEE, pp 1192–1195. doi:10.1109/ICPR.2010.297

  92. Murphy-Chutorian E, Trivedi M (2009) Head pose estimation in computer vision: a survey. Pattern Anal Mach Intell IEEE Trans 31(4):607–626

  93. Ojala T, Pietikainen M (2002) Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. Pattern Anal Mach Intell IEEE Trans 24(7):971–987

  94. O’Toole A, Vetter T, Troje N, Bulthoff H (1997) Sex classification is better with three-dimensional head structure than with image intensity information. Perception 26:75

  95. Ozbudak O, Kirci M, Cakir Y, Gunes E (2010) Effects of the facial and racial features on gender classification. In: MELECON 2010–2010 15th IEEE Mediterranean Electrotechnical Conference, pp 26–29

  96. Phillips P, Moon H, Rizvi S, Rauss P (2000) The FERET evaluation methodology for face-recognition algorithms. Pattern Anal Mach Intell IEEE Trans 22(10):1090–1104

  97. Phillips PJ, Flynn PJ, Scruggs T, Bowyer KW, Chang J, Hoffman K, Marques J, Min J, Worek W (2005) Overview of the face recognition grand challenge. In: Computer vision and pattern recognition, 2005. CVPR 2005. IEEE computer society conference on, pp 947–954

  98. Phung SL, Bouzerdoum A (2007) A pyramidal neural network for visual pattern recognition. IEEE Trans Neural Netw 18(2):329–43. doi:10.1109/TNN.2006.884677

  99. Rai P, Khanna P (2010) Gender classification using radon and wavelet transforms. In: Industrial and information systems (ICIIS), 2010 international conference on. IEEE, pp 448–451

  100. Rai P, Khanna P (2014) A gender classification system robust to occlusion using Gabor features based (2D)2PCA. J Vis Commun Image Represent 25(5):1118–1129. doi:10.1016/j.jvcir.2014.03.009

  101. Ramón-Balmaseda E, Lorenzo-Navarro J, Castrillón-Santana M (2012) Gender classification in large databases. In: Progress in pattern recognition, image analysis, computer vision, and applications, pp 74–81. doi:10.1007/978-3-642-33275-3_9

  102. Ricanek K, Tesafaye T (2006) Morph: a longitudinal image database of normal adult age-progression. In: Automatic face and gesture recognition, 2006. FGR 2006. 7th International conference on. IEEE, pp 341–345

  103. Riesenhuber M, Poggio T (1999) Hierarchical models of object recognition in cortex. Nat Neurosci 2(11):1019–25. doi:10.1038/14819

  104. Rojas-Bello RN, Lago-Fernandez LF, Martinez-Munoz G, Sdnchez-Montanes MA (2011) A comparison of techniques for robust gender recognition. In: 2011 18th IEEE international conference on image processing. IEEE, pp 561–564. doi:10.1109/ICIP.2011.6116610

  105. Ross A, Chen C (2011) Can gender be predicted from near-infrared face images? In: Image analysis and recognition, pp 120–129 (2011)

  106. Roweis S, Saul L (2000) Nonlinear dimensionality reduction by locally linear embedding. Science 290(5500):2323–2326

  107. Saatci Y, Town C (2006) Cascaded classification of gender and facial expression using active appearance models. In: Automatic face and gesture recognition, 2006. FGR 2006. 7th International conference on, pp 393–398

  108. Scalzo F, Bebis G, Nicolescu M, Loss L, Tavakkoli A (2008) Feature fusion hierarchies for gender classification. In: Pattern Recognition, 2008. ICPR 2008. 19th International conference on, Section 2. IEEE, pp 1–4 (2008)

  109. Shakhnarovich G, Viola P, Moghaddam B (2002) A unified learning framework for real time face detection and classification. In: Proceedings of Fifth IEEE international conference on automatic face gesture recognition, pp 16–23. doi:10.1109/AFGR.2002.1004124

  110. Shan C (2012) Learning local binary patterns for gender classification on real-world face images. Pattern Recognit Lett 33(4):431–437. doi:10.1016/j.patrec.2011.05.016

  111. Shen BC, Chen CS, Hsu HH (2009) Fast gender recognition by using a shared-integral-image approach. In: Acoustics, speech and signal processing, 2009. ICASSP 2009. IEEE international conference on, pp 521–524

  112. Shen H, Ma L, Zhang Q (2010) Gender categorization based on 3D faces. In: 2010 2nd International conference on advanced computer control. IEEE, pp 617–620. doi:10.1109/ICACC.2010.5487127

  113. Shih HC (2013) Robust gender classification using a precise patch histogram. Pattern Recognit 46(2):519–528. doi:10.1016/j.patcog.2012.08.003

  114. Shobeirinejad A, Gao Y (2010) Gender classification using interlaced derivative patterns. In: 2010 20th International conference on pattern recognition. IEEE, pp 1509–1512. doi:10.1109/ICPR.2010.1118

  115. Sim T, Baker S, Bsat M (2002) The CMU pose, illumination, and expression (PIE) database. In: Proceedings of Fifth IEEE international conference on automatic face gesture recognition. IEEE, pp 53–58. doi:10.1109/AFGR.2002.1004130

  116. Sun Z, Bebis G, Yuan X, Louis S (2002) Genetic feature subset selection for gender classification: a comparison study. In: Applications of computer vision, 2002. (WACV 2002). Proceedings Sixth IEEE Workshop on. IEEE, pp 165–170

  117. Tamura S, Kawai H, Mitsumoto H (1996) Male/female identification from 8x6 very low resolution face images by neural network. Pattern Recognit 29(2):331–335

    Article  Google Scholar 

  118. Tapia JE, Perez CA (2013) Gender classification based on fusion of different spatial scale features selected by mutual information from histogram of LBP, intensity, and shape. IEEE Trans Inf Forensics Secur 8(3):488–499. doi:10.1109/TIFS.2013.2242063

    Article  Google Scholar 

  119. Tapia JE, Perez CA (2013) Gender classification using one half face and feature selection based on mutual information. In: 2013 IEEE international conference on systems, man, and cybernetics, pp 3282–3287. doi:10.1109/SMC.2013.559

  120. Tariq U, Hu Y, Huang T (2009) Gender and ethnicity identification from silhouetted face profiles. In: Image processing (ICIP), 2009 16th IEEE international conference on. IEEE, pp 2441–2444

  121. Tivive FHC, Bouzerdoum A (2006) A gender recognition system using shunting inhibitory convolutional neural networks. In: The 2006 IEEE international joint conference on neural network proceedings. IEEE, pp 5336–5341. doi:10.1109/IJCNN.2006.247311

  122. Toderici G, O’Malley SM, Passalis G, Theoharis T, Kakadiaris IA (2010) Ethnicity- and gender-based subject retrieval using 3-D face-recognition techniques. Int J Comput Vis 89(2–3):382–391. doi:10.1007/s11263-009-0300-7

  123. Ueki K, Kobayashi T (2008) Gender classification based on integration of multiple classifiers using various features of facial and neck images. Inf Media Technol 3(2):479–485

  124. Ullah I, Hussain M (2012) Gender recognition from face images with dyadic wavelet transform and local binary pattern. In: Advances in Visual Computing, pp 409–419. doi:10.1007/978-3-642-33191-6_40

  125. Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. In: Computer vision and pattern recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE computer society conference on, vol 1, pp I-511-518

  126. Viola P, Jones MJ (2004) Robust real-time face detection. Int J Comput Vis 57(2):137–154. doi:10.1023/B:VISI.0000013087.49260.fb

  127. Wang J, Li J, Lee C, Yau W (2010) Dense SIFT and Gabor descriptors-based face representation with applications to gender recognition. In: Control automation robotics & vision (ICARCV), 2010 11th International conference on. IEEE, pp 1860–1864

  128. Wang J, Li J, Yau W, Sung E (2010) Boosting dense SIFT descriptors and shape contexts of face images for gender recognition. In: Computer vision and pattern recognition workshops (CVPRW), 2010 IEEE computer society conference on. IEEE, pp 96–102

  129. Wang J, Yau W (2014) Real-time moustache detection by combining image decolorization and texture detection with applications to facial gender recognition. Mach Vis Appl 25(4):1089–1099

  130. Wang Y, Ricanek K, Chen C, Chang Y (2010) Gender classification from infants to seniors. In: Biometrics: theory applications and systems (BTAS), 2010 Fourth IEEE international conference on, pp 1–6 (2010)

  131. Wiskott L, Fellous JM, Kruger N, Bochum RU, Angeles L (1995) Face recognition and gender determination, pp 92–97

  132. Wright J, Yang AY, Ganesh A, Sastry SS, Ma Y (2009) Robust face recognition via sparse representation. IEEE Trans Pattern Anal Mach Intell 31(2):210–227. doi:10.1109/TPAMI.2008.79

  133. Wu J, Smith WAP, Hancock ER (2011) Gender discriminating models from facial surface normals. Pattern Recognit 44(12):2871–2886. doi:10.1016/j.patcog.2011.04.013

  134. Wu TX, Lian XC, Lu BL (2011) Multi-view gender classification using symmetry of facial images. In: Neural computing and applications. Springer, Berlin, pp 1–9

  135. Xia B, Amor BB, Huang D, Daoudi M, Wang Y, Drira H (2013) Enhancing gender classification by combining 3D and 2D face modalities. In: Signal processing conference (EUSIPCO), 2013 Proceedings of the 21st European, pp 3–7

  136. Xia B, Sun H, Lu Bl (2008) Multi-view gender classification based on local Gabor binary mapping pattern and support vector machines. In: Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on, pp 3388–3395

  137. Xu Z, Lu L, Shi P (2008) A hybrid approach to gender classification from face images. In: Pattern recognition, 2008. ICPR 2008. 19th International conference on. IEEE, pp 1–4

  138. Yang J, Jiao Y, Xiong N, Park D (2013) Fast face gender recognition by using local ternary pattern and extreme learning machine. KSII Trans Internet Inf Syst (TIIS) 7(7):1705–1720

  139. Yang J, Zhang D, Frangi AF, Yang JY (2004) Two-dimensional PCA: a new approach to appearance-based face representation and recognition. IEEE Trans Pattern Anal Mach Intell 26(1):131–137. doi:10.1109/TPAMI.2004.10004

  140. Yang W, Chen C, Ricanek K, Sun C (2011) Gender classification via global-local features fusion. In: Biometric recognition, pp 214–220. doi:10.1007/978-3-642-25449-9_27

  141. Yang W, Sethuram A, Patternson E, Ricanek K, Sun C (2011) Gender classification using the profile. In: Advances in Neural Networks-ISNN 2011, pp 288–295

  142. Yang Z, Ai H (2007) Demographic classification with local binary patterns. In: Advances in Biometrics, pp 464–473

  143. Yao B, Bradski G, Fei-Fei L (2012) A codebook-free and annotation-free approach for fine-grained image categorization. In: 2012 IEEE conference on computer vision and pattern recognition. IEEE, pp 3466–3473. doi:10.1109/CVPR.2012.6248088

  144. Ylioinas J, Hadid A, Pietikäinen M (2011) Combining contrast information and local binary patterns for gender classification. In: Image Analysis, pp 676–686 (2011)

  145. Zafeiriou S, Tefas A, Pitas I (2008) Gender determination using a support vector machine variant. In: 16th European signal processing conference (EUSIPCO-2008), Lausanne, Switzerland, Eusipco, pp 2–6

  146. Zhang C, Zhang Z (2010) A survey of recent advances in face detection. In: Microsoft Research. http://research.microsoft.com/en-us/um/people/chazhang/publications/tr2010-66_chazhang.pdf. Accessed 18 Mar 2012

  147. Zhang G, Wang Y (2011) Hierarchical and discriminative bag of features for face profile and ear based gender classification. In: 2011 International joint conference on biometrics (IJCB), pp 1–8. doi:10.1109/IJCB.2011.6117590

  148. Zhang T, Tao D, Li X, Yang J (2009) Patch alignment for dimensionality reduction. Knowl Data Eng IEEE Trans 21:1299–1313

  149. Zheng J, Lu Bl (2011) A support vector machine classifier with automatic confidence and its application to gender classification. Neurocomputing 74(11):1926–1935. doi:10.1016/j.neucom.2010.07.032

  150. Zhou LB, Wang H (2012) Local gradient increasing pattern (LGIP) for facial representation and gender recognition. In: Image analysis and recognition, pp 46–53

Download references

Acknowledgments

C.B. Ng gratefully acknowledges the support from Universiti Tunku Abdul Rahman Staff Scholarship Fund.

Author information

Authors and Affiliations

  1. Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia

    Choon-Boon Ng, Yong-Haur Tay & Bok-Min Goi

Authors
  1. Choon-Boon Ng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong-Haur Tay
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bok-Min Goi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Choon-Boon Ng.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ng, CB., Tay, YH. & Goi, BM. A review of facial gender recognition. Pattern Anal Applic 18, 739–755 (2015). https://doi.org/10.1007/s10044-015-0499-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10044-015-0499-6

Keywords

Search

Navigation