Abstract
Automatic facial kinship verification is a challenging topic in computer vision due to its complexity and its important role in many applications such as finding missing children and forensics. This paper presents a Facial Kinship Verification (FKV) approach based on an automatic and more efficient two-step learning into color/texture information. Most of the proposed methods in automatic kinship verification from face images consider the luminance information only (i.e. gray-scale) and exclude the chrominance information (i.e. color) that can be helpful, as an additional cue, for predicting relationships. We explore the joint use of color-texture information from the chrominance and the luminance channels by extracting complementary low-level features from different color spaces. More specifically, the features are extracted from each color channel of the face image and fused to achieve better discrimination. We investigate different descriptors on the existing face kinship databases, illustrating the usefulness of color information, compared with the gray-scale counterparts, in seven various color spaces. Especially, we generate from each color space three subspaces projection matrices and then score fusion methodology to fuse three distances belonging to each test pair face images. Experiments on three benchmark databases, namely the Cornell KinFace, the KinFaceW (I & II) and the TSKinFace database, show superior results compared to the state of the art.











Similar content being viewed by others
References
Alirezazadeh P, Fathi A, Abdali-Mohammadi F (2015) A genetic algorithm-based feature selection for kinship verification. IEEE Signal Process Lett 22(12):2459–2463. https://doi.org/10.1109/LSP.2015.2490805
Alvergne A, Oda R, Faurie C, Matsumoto-Oda A, Durand V, Raymond M (2009) Cross-cultural perceptions of facial resemblance between kin. J Vis 9(6):23. https://doi.org/10.1167/9.6.23
Bleyer M, Chambon S, Poppe U, Gelautz M (2008) Evaluation of different methods for using colour information in global stereo matching approaches. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVII, Part B3a, pp 415–420. Vol. XXXVII, Part B3a, Beijing. http://publik.tuwien.ac.at/files/PubDat_169068.pdf. Vortrag: ISPRS Congress Beijing 2008, Beijing - China; 2008-07-03 – 2008-07-11
Brahnam S, Jain C, L, Nanni L, Lumini A (2014) Local Binary Patterns: New Variants and Applications, vol 506
Chan CH, Kittler J, Poh N, Ahonen T, Pietikäinen M (2009) (multiscale) local phase quantisation histogram discriminant analysis with score normalisation for robust face recognition. In: 2009 IEEE 12th international conference on computer vision workshops, ICCV workshops, pp 633–640. https://doi.org/10.1109/ICCVW.2009.5457642
Chan CH, Tahir MA, Kittler J, Pietikäinen M. (2013) Multiscale local phase quantization for robust component-based face recognition using kernel fusion of multiple descriptors. IEEE Trans Pattern Anal Mach Intell 35(5):1164–1177. https://doi.org/10.1109/TPAMI.2012.199
Choi JY, Ro YM, Plataniotis KN (2009) Color face recognition for degraded face images. IEEE Trans Syst Man Cybern B (Cybern) 39(5):1217–1230. https://doi.org/10.1109/TSMCB.2009.2014245
Dal Martello MF, Maloney LT (2006) Where are kin recognition signals in the human face? J Vis 6(12):2. https://doi.org/10.1167/6.12.2
DeBruine LM, Smith FG, Jones BC, Roberts SC, Petrie M, Spector TD (2009) Kin recognition signals in adult faces. Vis Res 49 (1):38–43. https://doi.org/10.1016/j.visres.2008.09.025. http://www.sciencedirect.com/science/article/pii/S0042698908004707
Dehghan A, Ortiz EG, Villegas R, Shah M (2014) Who do i look like? determining parent-offspring resemblance via gated autoencoders. In: 2014 IEEE Conference on computer vision and pattern recognition, pp 1757–1764. https://doi.org/10.1109/CVPR.2014.227
Draper BA, Baek K, Bartlett MS, Beveridge J (2003) Recognizing faces with pca and ica. Comput Vis Image Underst 91(1):115–137. https://doi.org/10.1016/S1077-3142(03)00077-8. http://www.sciencedirect.com/science/article/pii/S1077314203000778. Special Issue on Face Recognition
Fang R, Tang KD, Snavely N, Chen T (2010) Towards computational models of kinship verification. In: 2010 IEEE International conference on image processing, pp 1577–1580. https://doi.org/10.1109/ICIP.2010.5652590
Guo Y, Dibeklioglu H, van der Maaten L (2014) Graph-based kinship recognition. In: 2014 22nd international conference on pattern recognition, pp 4287–4292. https://doi.org/10.1109/ICPR.2014.735
Harrell FE Jr (2015) Regression modeling strategies: with applications to linear models, logistic and ordinal regression, and survival analysis. Springer
Hu J, Lu J, Tan YP (2014) Discriminative deep metric learning for face verification in the wild. In: Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, CVPR ’14. https://doi.org/10.1109/CVPR.2014.242. IEEE Computer Society, Washington, DC, pp 1875–1882
Hu J, Lu J, Yuan J, Tan YP (2015) Large margin multi-metric learning for face and kinship verification in the wild. Springer International Publishing, Cham, pp 252–267. https://doi.org/10.1007/978-3-319-16811-1_17
Huajie J, Lichun W, Yanfeng S, Yongli H (2012) Color face recognition based on color space normalization and quaternion matrix representation. In: 2012 4th international conference on digital home, pp 133–137. https://doi.org/10.1109/ICDH.2012.19
Hyvärinen A, Hurri J, Hoyer PO (2009) Natural image statistics: a probabilistic approach to early computational vision, vol 39
Kaminski G, Dridi S, Graff C, Gentaz E (2009) Human ability to detect kinship in strangers’ faces: effects of the degree of relatedness. Proc R Soc Lond B Biol Sci 276(1670):3193–3200. https://doi.org/10.1098/rspb.2009.0677. http://rspb.royalsocietypublishing.org/content/276/1670/3193
Kaminski G, Ravary F, Graff C, Gentaz E (2010) Firstborns’ disadvantage in kinship detection. Psychol Sci 21(12):1746–1750. https://doi.org/10.1177/0956797610388045. PMID: 21051523
Kannala J, Rahtu E (2012) Bsif: Binarized statistical image features. In: Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), pp 1363–1366
Liu C (2014) Discriminant analysis and similarity measure. Pattern Recogn 47 (1):359–367. https://doi.org/10.1016/j.patcog.2013.06.023 https://doi.org/10.1016/j.patcog.2013.06.023. http://www.sciencedirect.com/science/article/pii/S0031320313002756
Liu Q, Puthenputhussery A, Liu C (2015) Inheritable fisher vector feature for kinship verification. In: 2015 IEEE 7th international conference on biometrics theory, applications and systems (BTAS), pp 1–6. https://doi.org/10.1109/BTAS.2015.7358768
Liu Z, Liu C (2008) Fusion of the complementary discrete cosine features in the yiq color space for face recognition. Comput Vis Image Underst 111(3):249–262. https://doi.org/10.1016/j.cviu.2007.12.002. http://www.sciencedirect.com/science/article/pii/S1077314207001683
Lu J, Hu J, Tan YP (2017) Discriminative deep metric learning for face and kinship verification. IEEE Trans Image Process 26(9):4269–4282. https://doi.org/10.1109/TIP.2017.2717505
Lu J, Zhou X, Tan YP, Shang Y, Zhou J (2014) Neighborhood repulsed metric learning for kinship verification. IEEE Trans Pattern Anal Mach Intell 36(2):331–345. https://doi.org/10.1109/TPAMI.2013.134
Meina Kan Shiguang Shan DX, Chen X (2011) Side-information based linear discriminant analysis for face recognition. In: Proc. BMVC, pp 125.1–125.0. https://doi.org/10.5244/C.25.125
Nosaka R, Ohkawa Y, Fukui K (2012) Feature extraction based on co-occurrence of adjacent local binary patterns. Springer, Berlin, pp 82–91. https://doi.org/10.1007/978-3-642-25346-1_8
Ojansivu V, Heikkilä J (2008) Blur insensitive texture classification using local phase quantization. Springer, Berlin, pp 236–243. https://doi.org/10.1007/978-3-540-69905-7_27
Ouamane A, Bengherabi M, Hadid A, Cheriet M (2015) Side-information based exponential discriminant analysis for face verification in the wild. In: 2015 11th IEEE international conference and workshops on automatic face and gesture recognition (FG), vol 02, pp 1–6. https://doi.org/10.1109/FG.2015.7284837
Ouamane A, Messaoud B, Guessoum A, Hadid A, Cheriet M (2014) Multi scale multi descriptor local binary features and exponential discriminant analysis for robust face authentication. In: 2014 IEEE International conference on image processing (ICIP), pp 313–317. https://doi.org/10.1109/ICIP.2014.7025062
Qin X, Tan X, Chen S (2015) Tri-subject kinship verification: Understanding the core of a family. IEEE Trans Multimed 17(10):1855–1867. https://doi.org/10.1109/TMM.2015.2461462
Shao M, Xia S, Fu Y (2011) Genealogical face recognition based on ub kinface database. In: CVPR 2011 WORKSHOPS, pp 60–65. https://doi.org/10.1109/CVPRW.2011.5981801
Shao M, Xia S, Fu Y (2014) Identity and kinship relations in group pictures. Springer International Publishing, Cham, pp 175–190. https://doi.org/10.1007/978-3-319-05491-9_9
Sturm RA, Box NF, Ramsay M (1998) Human pigmentation genetics: the difference is only skin deep. BioEssays 20(9):712–721. https://doi.org/10.1002/(SICI)1521-1878(199809)20:9<712::AID-BIES4>3.0.CO;2-I
Torres L, Reutter JY, Lorente L (1999) The importance of the color information in face recognition. In: Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348), vol 3, pp 627–631. https://doi.org/10.1109/ICIP.1999.817191
Wu F, Jing XY, Dong X, Ge Q, Wu S, Liu Q, Yue D, Yang J (2016) Uncorrelated multi-set feature learning for color face recognition. Pattern Recogn 60:630–646. https://doi.org/10.1016/j.patcog.2016.06.010. http://www.sciencedirect.com/science/article/pii/S0031320316301261
Wu X, Boutellaa E, López M. B., Feng X, Hadid A (2016) On the usefulness of color for kinship verification from face images. In: 2016 IEEE International workshop on information forensics and security (WIFS), pp 1–6. https://doi.org/10.1109/WIFS.2016.7823901
Xia S, Shao M, Fu Y (2011) Kinship verification through transfer learning. In: Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence - Volume Volume Three, IJCAI’11, pp 2539–2544. AAAI Press. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-422
Xia S, Shao M, Luo J, Fu Y (2012) Understanding kin relationships in a photo. IEEE Trans Multimed 14(4):1046–1056. https://doi.org/10.1109/TMM.2012.2187436
Yan H (2017) Kinship verification using neighborhood repulsed correlation metric learning. Image Vision Comput 60(C):91–97. https://doi.org/10.1016/j.imavis.2016.08.009
Yan H, Lu J, Deng W, Zhou X (2014) Discriminative multimetric learning for kinship verification. IEEE Trans Inf Forensic Secur 9(7):1169–1178. https://doi.org/10.1109/TIFS.2014.2327757
Yan H, Lu J, Zhou X (2015) Prototype-based discriminative feature learning for kinship verification. IEEE Trans Cybern 45(11):2535–2545. https://doi.org/10.1109/TCYB.2014.2376934
Yang J, Liu C (2008) Color image discriminant models and algorithms for face recognition. IEEE Trans Neural Netw 19(12):2088–2098. https://doi.org/10.1109/TNN.2008.2003187
Yip AW, Sinha P (2002) Contribution of color to face recognition. Perception 31(8):995–1003. https://doi.org/10.1068/p3376. PMID: 12269592
Zhang T, Fang B, Tang YY, Shang Z, Xu B (2010) Generalized discriminant analysis: A matrix exponential approach. IEEE Trans Syst Man Cybern B (Cybern) 40(1):186–197. https://doi.org/10.1109/TSMCB.2009.2024759
Zhao M, Zhang Z, Chow TW, Li B (2014) Soft label based linear discriminant analysis for image recognition and retrieval. Comput Vis Image Underst 121(Supplement C):86–99. https://doi.org/10.1016/j.cviu.2014.01.008. http://www.sciencedirect.com/science/article/pii/S1077314214000150
Zhou X, Hu J, Lu J, Shang Y, Guan Y (2011) Kinship verification from facial images under uncontrolled conditions. In: Proceedings of the 19th ACM International Conference on Multimedia, MM ’11. ACM, New York, pp 953–956. https://doi.org/10.1145/2072298.2071911
Zhou X, Shang Y, Yan H, Guo G (2016) Ensemble similarity learning for kinship verification from facial images in the wild. Inf Fusion 32(PB):40–48. https://doi.org/10.1016/j.inffus.2015.08.006
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix: Detailled results of color spaces on the five databases
Appendix: Detailled results of color spaces on the five databases
Tables 4 5, 6 and 7 provide the detailed mean accuracy of kinship verification of different descriptors and color spaces on the Cornell, TSKinFace, KinFaceW-I and KinFaceW-II databases, respectively. The values in the tables are the kinship verification rates (accuracy in %).
Rights and permissions
About this article
Cite this article
Laiadi, O., Ouamane, A., Boutellaa, E. et al. Kinship verification from face images in discriminative subspaces of color components. Multimed Tools Appl 78, 16465–16487 (2019). https://doi.org/10.1007/s11042-018-7027-9
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-018-7027-9