1.
Arandjelovic, O., Shakhnarovich, G., Fisher, J., Cipolla, R., Darrell, T.: Face recognition with image sets using manifold density divergence. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, pp. 581–588. IEEE (2005)
2.
Baudat, G., Anouar, F.: Generalized discriminant analysis using a kernel approach. Neural Comput.
12(10), 2385–2404 (2000)
CrossRef
3.
Cevikalp, H., Triggs, B., Face recognition based on image sets. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2567–2573. IEEE (2010)
4.
Chen, S., Sanderson, C., Harandi, M.T., Lovell, B.C.: Improved image set classification via joint sparse approximated nearest subspaces. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 452–459. IEEE (2013)
5.
Chen, S., Wiliem, A., Sanderson, C., Lovell, B.C.: Matching image sets via adaptive multi convex hull. In: 2014 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1074–1081. IEEE (2014)
6.
Chen, Z., Jiang, B., Tang, J., Luo, B.: Image set representation and classification with covariate-relation graph. In: IEEE Conference on Asian Conference and Pattern Recognition, ACPR 2015, pp. 750–754. IEEE (2015)
7.
Cui, Z., Shan, S., Zhang, H., Lao, S., Chen, X.: Image sets alignment for video-based face recognition. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2626–2633. IEEE (2012)
8.
Gross, R., Shi, J.: The CMU motion of body (MoBo) database. Technical report CMU-RI-TR-01-18, Robotics Institute, Carnegie Mellon University (2001)
9.
Hamm, J., Lee, D.D.: Grassmann discriminant analysis: a unifying view on subspace-based learning. In: Proceedings of the 25th International Conference on Machine Learning, pp. 376–383. ACM (2008)
10.
Harandi, M.T., Sanderson, C., Shirazi, S., Lovell, B.C.: Graph embedding discriminant analysis on Grassmannian manifolds for improved image set matching. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2705–2712. IEEE (2011)
11.
Hu, Y., Mian, A.S., Owens, R.: Sparse approximated nearest points for image set classification. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 121–128. IEEE (2011)
12.
Ke, Q., Kanade, T.: Robust L1 norm factorization in the presence of outliers and missing data by alternative convex programming. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), pp. 739–746. IEEE (2005)
13.
Kim, M., Kumar, S., Pavlovic, V., Rowley, H.: Face tracking and recognition with visual constraints in real-world videos. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, pp. 1–8. IEEE (2008)
14.
Kim, T.-K., Kittler, J., Cipolla, R.: Discriminative learning and recognition of image set classes using canonical correlations. IEEE Trans. Pattern Anal. Mach. Intell.
29(6), 1005–1018 (2007)
CrossRef
15.
Lee, K.C., Ho, J., Yang, M.H., Kriegman, D.: Video-based face recognition using probabilistic appearance manifolds. In: Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 313–320 (2003)
16.
Leibe, B., Schiele, B.: Analyzing appearance and contour based methods for object categorization. In: Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 409–415. IEEE (2003)
17.
Liu, G., Lin, Z., Yu, Y.: Robust subspace segmentation by low-rank representation. In: Proceedings of the 27th International Conference on Machine Learning (ICML 2010), pp. 663–670 (2010)
18.
Lu, J., Wang, G., Moulin, P.: Image set classification using holistic multiple order statistics features and localized multi-kernel metric learning. In: 2013 IEEE International Conference on Computer Vision (ICCV), pp. 329–336. IEEE (2013)
19.
Nie, F., Huang, H., Cai, X., Ding, C.H.: Efficient and robust feature selection via joint 2, 1-norms minimization. In: Advances in Neural Information Processing Systems, pp. 1813–1821 (2010)
20.
Nishiyama, M., Yamaguchi, O., Fukui, K.: Face recognition with the multiple constrained mutual subspace method. In: Kanade, T., Jain, A., Ratha, N.K. (eds.) AVBPA 2005. LNCS, vol. 3546, pp. 71–80. Springer, Heidelberg (2005). doi:
10.1007/11527923_8
CrossRef
21.
Shakhnarovich, G., Fisher, J.W., Darrell, T.: Face recognition from long-term observations. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2352, pp. 851–865. Springer, Heidelberg (2002). doi:
10.1007/3-540-47977-5_56
CrossRef
22.
Wang, R., Chen, X.: Manifold discriminant analysis. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 429–436. IEEE (2009)
23.
Wang, R., Guo, H., Davis, L.S., Dai, Q.: Covariance discriminative learning: a natural and efficient approach to image set classification. In:2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2496–2503. IEEE (2012)
24.
Wang, R., Shan, S., Chen, X., Gao, W.: Manifold-manifold distance with application to face recognition based on image set. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, pp. 1–8. IEEE (2008)
25.
Wang, W., Wang, R., Huang, Z., Shan, S., Chen, X.: Discriminant analysis on Riemannian manifold of Gaussian distributions for face recognition with image sets. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2048–2057 (2015)
26.
Yamaguchi, O., Fukui, K., Maeda, K.-I.: Face recognition using temporal image sequence. In: Proceedings of the Third IEEE International Conference on Automatic Face and Gesture Recognition, pp. 318–323. IEEE (1998)
27.
Yang, M., Zhu, P., Van Gool, L., Zhang, L.: Face recognition based on regularized nearest points between image sets. In: 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), pp. 1–7. IEEE (2013)
28.
Yu, L., Zhang, M., Ding, C.: An efficient algorithm for L1-norm principal component analysis. In: 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1377–1380. IEEE (2012)
29.
Zhu, P., Zhang, L., Zuo, W., Zhang, D.: From point to set: extend the learning of distance metrics. In: 2013 IEEE International Conference on Computer Vision (ICCV), pp. 2664–2671. IEEE (2013)