Abstract
Kinship verification between aged parents and their children based on facial images is a challenging problem, due to aging factor which makes their facial similarities less distinct. In this paper, we propose to perform kinship verification in a transfer learning manner, which introduces photos of parents in their earlier ages as intermediate references to facilitate the verification. Child-young parent pairs are regarded as source domain and child-old parent ones are considered as target domain. The transfer learning scheme contains two phases. In the transfer metric learning phase, the extracted locality-constrained sparse features of images are projected into an optimized subspace where the intra-class distances are minimized and the inter-class ones are maximized. In the transfer classifier learning phase, a cross domain classifier is learned by a transfer SVM algorithm. Experimental results on UB KinFace dataset indicate that our method outperforms state-of-the-art methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: application to face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 28(12), 2037–2041 (2006)
Dibeklioglu, H., Salah, A.A., Gevers, T.: Like father, like son: facial expression dynamics for kinship verification. In: 2013 IEEE International Conference on Computer Vision (ICCV), pp. 1497–1504. IEEE (2013)
Fang, R., Gallagher, A., Chen, T., Loui, A.: Kinship classification by modeling facial feature heredity. In: 20th IEEE International Conference on Image Processing (ICIP), pp. 2983–2987. IEEE (2013)
Fang, R., Tang, K.D., Snavely, N., Chen, T.: Towards computational models of kinship verification. In: 17th IEEE International Conference on Image Processing (ICIP), pp. 1577–1580. IEEE (2010)
Guo, G., Wang, X.: Kinship measurement on salient facial features. IEEE Trans. Instrum. Meas. 61(8), 2322–2325 (2012)
Guo, Y., Dibeklioglu, H., van der Maaten, L.: Graph-based kinship recognition. In: 22nd International Conference on Pattern Recognition (ICPR) 2014, pp. 4287–4292. IEEE (2014)
Long, M., Wang, J., Ding, G., Pan, S.J., Yu, P.S.: Adaptation regularization: a general framework for transfer learning. IEEE Trans. Knowl. Data Eng. 26(5), 1076–1089 (2014)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)
Lu, J., Zhou, X., Tan, Y.P., Shang, Y., Zhou, J.: Neighborhood repulsed metric learning for kinship verification. IEEE Trans. Pattern Anal. Mach. Intell. 36(2), 331–345 (2014)
Qin, X., Tan, X., Chen, S.: Tri-subject kinship verification: understanding the core of a family. IEEE Trans. Multimedia 17(10), 1855–1867 (2015)
Quanz, B., Huan, J.: Large margin transductive transfer learning. In: Proceedings of the 18th ACM Conference on Information and Knowledge Management, pp. 1327–1336. ACM (2009)
Wang, J., Yang, J., Yu, K., Lv, F., Huang, T., Gong, Y.: Locality-constrained linear coding for image classification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3360–3367. IEEE (2010)
Xia, S., Shao, M., Fu, Y.: Kinship verification through transfer learning. In: IJCAI Proceedings-International Joint Conference on Artificial Intelligence, vol. 22, p. 2539 (2011)
Xia, S., Shao, M., Luo, J., Fu, Y.: Understanding kin relationships in a photo. IEEE Trans. Multimedia 14(4), 1046–1056 (2012)
Yan, H., Lu, J., Deng, W., Zhou, X.: Discriminative multimetric learning for kinship verification. IEEE Trans. Inf. Forensics Secur. 9(7), 1169–1178 (2014)
Yan, H.C., Lu, J., Zhou, X.: Prototype-based discriminative feature learning for kinship verification. IEEE Trans. Cybern. 45, 2535–2545 (2014)
Zhou, X., Hu, J., Lu, J., Shang, Y., Guan, Y.: Kinship verification from facial images under uncontrolled conditions. In: Proceedings of the 19th ACM International Conference on Multimedia, pp. 953–956. ACM (2011)
Zhou, X., Lu, J., Hu, J., Shang, Y.: Gabor-based gradient orientation pyramid for kinship verification under uncontrolled environments. In: Proceedings of the 20th ACM International Conference on Multimedia, pp. 725–728. ACM (2012)
Acknowledgments
This work was supported in part by the National Natural Science Foundation of China (No. 61472036).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Zhang, Y., Ma, B., Huang, L., Hu, H. (2015). Transfer Metric Learning for Kinship Verification with Locality-Constrained Sparse Features. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9489. Springer, Cham. https://doi.org/10.1007/978-3-319-26532-2_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-26532-2_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-26531-5
Online ISBN: 978-3-319-26532-2
eBook Packages: Computer ScienceComputer Science (R0)