Kinship Verification from Faces via Similarity Metric Based Convolutional Neural Network

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• 关键词：Kinship verification ; Similarity metric learning ; Convolutional neural networks ; Siamese architecture
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9730
• 期：1
• 页码：539-548
• 全文大小：830 KB
• 参考文献：1.Chopra, S., Hadsell, R., Lecun, Y.: Learning a similarity metric discriminatively, with application to face verification. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005. CVPR 2005, vol. 1, pp. 539–546 (2005)
  2.Fang, R., Tang, K.D., Snavely, N., Chen, T.: Towards computational models of kinship verification. In: Proceedings/ICIP. International Conference on Image Processing, pp. 1577–1580 (2010)
  3.Hinton, G.E., Osindero, S., Teh, Y.W.: A fast learning algorithm for deep belief nets. Neural Comput. 18(7), 1527–1554 (2006)MathSciNet CrossRef MATH
  4.Huang, G., Lee, H., Learned-Miller, E.: Learning hierarchical representations for face verification with convolutional deep belief networks. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2518–2525, June 2012
  5.Khalil-Hani, M., Sung, L.S.: A convolutional neural network approach for face verification. In: 2014 International Conference on High Performance Computing & Simulation (HPCS), pp. 707–714 (2014)
  6.Kou, L., Zhou, X., Xu, M., Shang, Y.: Learning a genetic measure for kinship verification using facial images. Math. Prob. Eng. 2015, 1–5 (2015)
  7.Lu, J., Zhou, X., Tan, Y.P., Shang, Y., Zhou, J.: Neighborhood repulsed metric learning for kinship verification. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2594–2601 (2012)
  8.Lu, J., Hu, J., Liong, V.E., Zhou, X., Bottino, A., Ul Islam, I., Figueiredo Vieira, T., Qin, X., Tan, X., Chen, S.: The FG 2015 kinship verification in the wild evaluation. In: 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG) (2015)
  9.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)CrossRef
  10.Mignon, A.: PCCA: a new approach for distance learning from sparse pairwise constraints. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 2666–2672 (2012)
  11.Palm, R.B.: Prediction as a candidate for learning deep hierarchical models of data (2012)
  12.Shuiwang, J., Ming, Y., Kai, Y.: 3D convolutional neural networks for human action recognition. IEEE Trans. Pattern Anal. Mach. Intell. 35(1), 221–231 (2013)CrossRef
  13.Taigman, Y., Yang, M., Ranzato, M., Wolf, L.: Deepface: closing the gap to human-level performance in face verification. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1701–1708 (2014)
  14.Xia, S., Shao, M., Luo, J., Fu, Y.: Understanding kin relationships in a photo. IEEE Trans. Multimed. 14(4), 1046–1056 (2012)CrossRef
  15.Yan, H., Lu, J., Deng, W., Zhou, X.: Discriminative multimetric learning for kinship verification. IEEE Trans. Inf. Forensics Secur. 9(7), 1169–1178 (2014)CrossRef
  16.Zhou, X., Lu, J., Hu, J., Shang, Y.: Gabor-based gradient orientation pyramid for kinship verification under uncontrolled environments. In: ACM International Conference on Multimedia, pp. 725–728 (2012)
  
• 作者单位：Lei Li (15)
  Xiaoyi Feng (15)
  Xiaoting Wu (15)
  Zhaoqiang Xia (15)
  Abdenour Hadid (15) (16)
  
  15. School of Electronics and Information, Northwestern Polytechnical University, Xi’an, 710129, Shaanxi, China
  16. Center for Machine Vision Research (CMVS), University of Oulu, Oulu, Finland
  
• 丛书名：Image Analysis and Recognition
• ISBN：978-3-319-41501-7
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9730

文摘

The ability to automatically determine whether two persons are from the same family or not is referred to as Kinship (or family) verification. This is a recent and challenging research topic in computer vision. We propose in this paper a novel approach to kinship verification from facial images. Our solution uses similarity metric based convolutional neural networks. The system is trained using Siamese architecture specific constraints. Extensive experiments on the benchmark KinFaceW-I & II kinship face datasets showed promising results compared to many state-of-the-art methods.