P. Viola and M. Jones, Fast multi-view face detection, In: CVPR, 2001.

J. Friedman, machine., The Annals of Statistics, vol.29, issue.5, pp.1189-1232, 2001.
DOI : 10.1214/aos/1013203451

T. G. Dietterich, R. H. Lathrop, and T. Lozano-perez, Solving the multiple instance problem with axis-parallel rectangles, Artificial Intelligence, vol.89, issue.1-2, 1997.
DOI : 10.1016/S0004-3702(96)00034-3

P. Viola, J. C. Platt, and C. Zhang, Multiple instance boosting for object detection, In: NIPS, 2005.

G. B. Huang, M. Ramesh, T. Berg, and E. Learned-miller, Labeled faces in the wild: A database for studying face recognition in unconstrained environments, 2007.

Y. Lecun, P. Haffner, L. Bottou, and Y. Bengio, Gradient-based learning applied to document recognition, Proceedings of the IEEE, vol.86, issue.11, 1998.
DOI : 10.1109/5.726791

M. Jones and P. Viola, Fast multi-view face detection, 2003.

C. Huang, H. Ai, Y. Li, and S. Lao, Vector boosting for rotation invariant multi-view face detection, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005.
DOI : 10.1109/ICCV.2005.246

E. Seemann, B. Leibe, and B. Schiele, Multi-Aspect Detection of Articulated Objects, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), 2006.
DOI : 10.1109/CVPR.2006.193

A. Torralba, K. Murphy, and W. Freeman, Sharing Visual Features for Multiclass and Multiview Object Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.5, pp.854-869, 2007.
DOI : 10.1109/TPAMI.2007.1055
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.2675

Z. Tu, Probabilistic Boosting-Tree: Learning Discriminative Models for Classification , Recognition, and Clustering, In: ICCV, 2005.

B. Wu and R. Nevatia, Cluster Boosted Tree Classifier for Multi-View, Multi-Pose Object Detection, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4409006
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.309.9885

E. Learned-miller, Data driven image models through continuous joint alignment, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.2, pp.236-250, 2006.
DOI : 10.1109/TPAMI.2006.34
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.84.3320

G. Huang, V. Jain, and E. Learned-miller, Unsupervised Joint Alignment of Complex Images, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408858

A. Vedaldi and S. Soatto, A Complexity-Distortion Approach to Joint Pattern Alignment, In: NIPS, vol.19, 2007.

M. Weber, M. Welling, and P. Perona, Unsupervised Learning of Models for Recognition, In: ECCV, 2000.
DOI : 10.1007/3-540-45054-8_2

R. Fergus, P. Perona, and A. Zisserman, Object class recognition by unsupervised scale-invariant learning, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., 2003.
DOI : 10.1109/CVPR.2003.1211479

D. J. Crandall and D. P. Huttenlocher, Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition, In: ECCV, 2006.
DOI : 10.1007/11744023_2

J. D. Keeler, D. E. Rumelhart, and W. K. Leow, Integrated segmentation and recognition of hand-printed numerals, In: NIPS, 1990.

S. Nowlan and J. Platt, A convolutional neural net. hand tracker, In: NIPS, 1995.

J. Friedman, T. Hastie, and R. Tibshirani, Additive logistic regression: a statistical view of boosting, 1998.

S. Boyd and L. Vandenberghe, Convex Optimization, 2004.

P. Dollár, Z. Tu, H. Tao, and S. Belongie, Feature Mining for Image Classification, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383046