Combined Features for Face Recognition in Surveillance Conditions-Reference-Cited by-同舟云学术

Combined Features for Face Recognition in Surveillance Conditions

Published:2014 Issue: Volume: Page:503-514
ISSN:0302-9743
Container-title:Neural Information Processing
language:
Short-container-title:

Author:

Assaleh Khaled,Shanableh Tamer,Abuqaaud Kamal

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-12640-1_61

Reference17 articles.

1. Chuu, T., Azmin, S.: A study on face recognition in video surveillance system using multi-class Support Vector Machines. In: TENCON 2011, IEEE Region 10 Conference, pp. 25–29 (2011)

2. Jain, A., Ross, A., Prabhakar, S.: An Introduction to Biometric Recognition. IEEE Transactions on Circuits and Systems for Video Technology 14(1), 4–20 (2004)

3. Li, S., Jain, K.: Hand book of face recognition. Springer, New York (2005)

4. Han, H., Shan, S., Chen, X., Gao, W.: A comparative Study on Illumination Preprocessing in Face Recognition. Pattern Recognition 46(6), 1691–1699 (2013)

5. Jiang, M., Feng, J.: Robust Low-rank Subspace Recovery and Face Image Denoising for Face Recognition. In: IEEE International Conference on Image Processing (ICIP), pp. 3033–3036 (September 2011)

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Face recognition via fast dense correspondence;Multimedia Tools and Applications;2017-03-11

2. Face Recognition Using Dense SIFT Feature Alignment;Chinese Journal of Electronics;2016-11

3. Learnt Quasi-Transitive Similarity for Retrieval from Large Collections of Faces;2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR);2016-06