S. Agarwal, A. Awan, and D. Roth, Learning to detect objects in images via a sparse, part-based representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.11, pp.1475-1490, 2004.
DOI : 10.1109/TPAMI.2004.108

T. Ahonen, A. Hadid, and M. Pietikainen, Face Description with Local Binary Patterns: Application to Face Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.12, pp.42-43, 2006.
DOI : 10.1109/TPAMI.2006.244

T. Ahonen and M. Pietikäinen, Soft histograms for local binary patterns, Proceedings of the Finnish signal processing symposium, pp.1-19, 2007.

I. Andrews, T. Tsochantaridis, and . Hofmann, Support vector machines for multipleinstance learning, Proceedings of the Neural Information and Processing Systems, pp.561-568, 2002.

S. Baker and S. Nayar, Pattern rejection, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p.18, 1996.
DOI : 10.1109/CVPR.1996.517125

A. Bar-hillel, D. Levi, E. Krupka, and C. Goldberg, Part-Based Feature Synthesis for Human Detection, Proceedings of the 10th European Conference on Computer Vision, pp.127-142, 2010.
DOI : 10.1007/978-3-642-15561-1_10

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.178.9368

O. Barinova, V. Lempitsky, and P. Kohli, On detection of multiple object instances using Hough transforms, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.2233-2240, 2010.

H. Bay, A. Ess, T. Tuytelaars, and L. Van-gool, Speeded-Up Robust Features (SURF), Computer Vision and Image Understanding, pp.346-359, 2008.
DOI : 10.1016/j.cviu.2007.09.014

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.205.738

I. Biederman, Recognition-by-components: A theory of human image understanding, Psychological review, pp.115-118, 1987.

M. Blaschko and C. Lampert, Learning to Localize Objects with Structured Output Regression, Proceedings of the 9th European Conference on Computer Vision, pp.2-15, 2008.
DOI : 10.1007/978-3-540-88682-2_2

A. Bordes, S. Ertekin, J. Weston, and L. Bottou, Fast kernel classifiers with online and active learning, In Journal of Machine Learning Research, vol.6, pp.1579-1619, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00752361

A. Bosch, A. Zisserman, and X. Munoz, Representing shape with a spatial pyramid kernel, Proceedings of the 6th ACM international conference on Image and video retrieval, CIVR '07, pp.401-408, 2007.
DOI : 10.1145/1282280.1282340

G. Bouchard and B. Triggs, Hierarchical Part-Based Visual Object Categorization, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.710-715, 2005.
DOI : 10.1109/CVPR.2005.174

URL : https://hal.archives-ouvertes.fr/inria-00548513

L. Bourdev and J. Brandt, Robust Object Detection via Soft Cascade, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), p.102, 2005.
DOI : 10.1109/CVPR.2005.310

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.190.3554

C. Cortes and V. Vapnik, Support-vector networks, Machine Learning, vol.1, issue.3, pp.273-297, 1995.
DOI : 10.1007/BF00994018

G. Csurka, C. Bray, C. Dance, and L. Fan, Visual categorization with bags of keypoints, Workshop on Statistical Learning in Computer Vision, ECCV, pp.1-22, 2004.

. Dalal, Finding People in Images and Videos, pp.31-32, 2006.
URL : https://hal.archives-ouvertes.fr/tel-00390303

N. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.886-893, 2005.
DOI : 10.1109/CVPR.2005.177

URL : https://hal.archives-ouvertes.fr/inria-00548512

S. De and J. , SIMPLS: an alternative approach to partial least squares regression, Chemometrics and Intelligent Laboratory Systems, pp.251-263, 1993.

D. Desai, C. Ramanan, and . Fowlkes, Discriminative models for multi-class object layout, Proceedings of the 12th IEEE International Conference on Computer Vision, pp.17-112, 2009.
DOI : 10.1007/s11263-011-0439-x

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.8585

P. Dollàr, B. Babenko, S. Belongie, P. Perona, and Z. Tu, Multiple Component Learning for Object Detection, Proceedings of the 9th European Conference on Computer Vision, pp.10-14, 2008.
DOI : 10.1007/978-3-540-88688-4_16

P. Dollár, Z. Tu, P. Perona, and S. Belongie, Integral Channel Features, Procedings of the British Machine Vision Conference 2009, p.83, 2010.
DOI : 10.5244/C.23.91

P. Dollár, C. Wojek, B. Schiele, and P. Perona, Pedestrian detection: A benchmark, 2009 IEEE Conference on Computer Vision and Pattern Recognition, p.33, 2009.
DOI : 10.1109/CVPR.2009.5206631

C. Elkan, Using the triangle inequality to accelerate K-Means, Proceedings of the 20th International Conference on Machine learning, pp.147-153, 2003.

A. Ess, B. Leibe, and L. V. , Depth and Appearance for Mobile Scene Analysis, 2007 IEEE 11th International Conference on Computer Vision, pp.81-105, 2007.
DOI : 10.1109/ICCV.2007.4409092

A. Ess, B. Leibe, K. Schindler, and L. Van-gool, A mobile vision system for robust multi-person tracking, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.81-105, 2008.
DOI : 10.1109/CVPR.2008.4587581

M. Everingham, L. Van-gool, C. Williams, C. Winn, and A. Zisserman, PASCAL Visual Object Classes Challenge results, 2010.
DOI : 10.1007/11736790_8

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.101.6521

M. Everingham, L. Van-gool, C. Williams, J. Winn, and A. Zisserman, The Pascal Visual Object Classes (VOC) Challenge, International Journal of Computer Vision, vol.73, issue.2, pp.303-338, 2010.
DOI : 10.1007/s11263-009-0275-4

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.167.6629

M. Everingham, L. Van-gool, C. Williams, and A. Zisserman, PASCAL Visual Object Classes Challenge results, p.37, 2006.

R. Fan, K. Chang, C. Hsieh, X. Wang, and C. Lin, LIBLINEAR: A library for large linear classification, In Journal of Machine Learning Research, vol.9, issue.65, pp.1871-1874, 2008.

P. Felzenszwalb, R. Girshick, and D. Mcallester, Cascade object detection with deformable part models, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.2241-2248
DOI : 10.1109/CVPR.2010.5539906

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.164.8688

P. Felzenszwalb, R. Girshick, and D. Mcallester, Discriminatively trained deformable part models, release 4, pp.96-97
DOI : 10.1109/cvpr.2008.4587597

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.686

P. Felzenszwalb, R. Girshick, D. Mcallester, and D. Ramanan, Object Detection with Discriminatively Trained Part-Based Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.86-93, 2009.
DOI : 10.1109/TPAMI.2009.167

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.153.2745

P. Felzenszwalb and D. Huttenlocher, Efficient matching of pictorial structures, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662), pp.66-75, 2000.
DOI : 10.1109/CVPR.2000.854739

P. Felzenszwalb and D. Huttenlocher, Pictorial Structures for Object Recognition, International Journal of Computer Vision, vol.61, issue.1, pp.55-79, 2005.
DOI : 10.1023/B:VISI.0000042934.15159.49

P. Felzenszwalb, D. Mcallester, and D. Ramanan, A discriminatively trained, multiscale, deformable part model, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.25-93, 2008.
DOI : 10.1109/CVPR.2008.4587597

R. Fergus, P. Perona, and A. Zisserman, Object class recognition by unsupervised scaleinvariant learning, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.5-14, 2003.
DOI : 10.1109/cvpr.2003.1211479

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.114.7863

R. Fergus, P. Perona, and A. Zisserman, A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), p.10, 2005.
DOI : 10.1109/CVPR.2005.47

M. Fischler and R. Elschlager, The Representation and Matching of Pictorial Structures, IEEE Transactions on Computers, pp.67-92, 1973.
DOI : 10.1109/T-C.1973.223602

W. Förstner, Reliability analysis of parameter estimation in linear models with applications to mensuration problems in computer vision, Computer Vision, Graphics and Image Processing, pp.273-310, 1987.

V. Franc and S. Sonnenburg, Optimized cutting plane algorithm for large-scale risk minimization, In Journal of Machine Learning Research, vol.10, pp.2157-2192, 2009.

Y. Freund and R. Schapire, A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting, Proceedings of Computational Learning Theory, pp.23-37, 1996.
DOI : 10.1006/jcss.1997.1504

G. Fung and O. L. Mangasarian, A Feature Selection Newton Method for Support Vector Machine Classification, Computational Optimization and Applications, vol.28, issue.2, p.66, 2002.
DOI : 10.1023/B:COAP.0000026884.66338.df

J. Gall and V. Lempitsky, Class-specific Hough forests for object detection, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.10-16, 2009.
DOI : 10.1109/cvpr.2009.5206740

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.9407

C. Garcia and M. Delakis, Convolutional face finder: a neural architecture for fast and robust face detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.11, pp.1408-1423, 2004.
DOI : 10.1109/TPAMI.2004.97

M. Gavrila and V. Philomin, Real-time object detection for "smart" vehicles, Proceedings of the Seventh IEEE International Conference on Computer Vision, pp.87-93, 1999.
DOI : 10.1109/ICCV.1999.791202

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.113.3059

D. Gerónimo, A. M. López, A. D. Sappa, and T. Graf, Survey of Pedestrian Detection for Advanced Driver Assistance Systems, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.7, pp.1239-1258, 2010.
DOI : 10.1109/TPAMI.2009.122

A. Gualdi, R. Prati, and . Cucchiara, Multi-stage Sampling with Boosting Cascades for Pedestrian Detection in Images and Videos, Proceedings of the 10th European Conference on Computer Vision, pp.196-209, 2010.
DOI : 10.1007/978-3-642-15567-3_15

A. Gupta, S. Satkin, A. A. Efros, and M. Hebert, From 3D scene geometry to human workspace, CVPR 2011, p.112, 2011.
DOI : 10.1109/CVPR.2011.5995448

. Haralick, Statistical and structural approaches to texture, Proceedings of the IEEE, pp.786-804, 1979.
DOI : 10.1109/PROC.1979.11328

H. Harzallah, F. Jurie, and C. Schmid, Combining efficient object localization and image classification, 2009 IEEE 12th International Conference on Computer Vision, pp.237-244, 2009.
DOI : 10.1109/ICCV.2009.5459257

URL : https://hal.archives-ouvertes.fr/inria-00439516

M. Heikkilä, M. Pietikäinen, and C. Schmid, Description of interest regions with local binary patterns, Pattern recognition, pp.425-436, 2009.
DOI : 10.1016/j.patcog.2008.08.014

S. Hussain and B. Triggs, Feature Sets and Dimensionality Reduction for Visual Object Detection, Procedings of the British Machine Vision Conference 2010, pp.112-113, 2010.
DOI : 10.5244/C.24.112

URL : https://hal.archives-ouvertes.fr/hal-00565024

S. Ioffe and D. A. Forsyth, Probabilistic methods for finding people, International Journal of Computer Vision, vol.43, issue.1, pp.45-68, 2001.
DOI : 10.1023/A:1011179004708

S. Ito and S. Kubota, Object classification using heterogeneous co-occurrence features, Proceedings of the 11th European conference on Computer vision: Part V, pp.701-714, 2010.
DOI : 10.1007/978-3-642-15552-9_16

A. Jain and F. Farrokhnia, Unsupervised texture segmentation using Gabor filters, Pattern recognition, pp.1167-1186, 1991.
DOI : 10.1109/icsmc.1990.142050

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.319.2001

V. Jain and E. Learned-miller, Online domain adaptation of a pre-trained cascade of classifiers, CVPR 2011, p.112, 2011.
DOI : 10.1109/CVPR.2011.5995317

T. Joachims, Making large-scale SVM learning practical, Advances in Kernel Methods -Support Vector Learning, pp.14-82, 1999.

T. Kadir and M. Brady, Scale, saliency and image description, International Journal of Computer Vision, vol.45, issue.2, pp.83-105, 2001.
DOI : 10.1023/A:1012460413855

A. Kembhavi, D. Harwood, and L. Davis, Vehicle Detection Using Partial Least Squares, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.6
DOI : 10.1109/TPAMI.2010.182

A. Kläser, Learning human actions in video, p.116, 2010.

A. Kläser, M. Marszalek, C. Schmid, and A. Zisserman, Human Focused Action Localization in Video, International Workshop on Sign, Gesture, and Activity (SGA) in Conjunction with ECCV, p.111, 2010.
DOI : 10.1007/978-3-642-35749-7_17

C. Lampert and M. Blaschko, A Multiple Kernel Learning Approach to Joint Multi-class Object Detection, Pattern Recognition, pp.31-40, 2008.
DOI : 10.1007/978-3-540-69321-5_4

C. Lampert, M. Blaschko, and T. Hofmann, Beyond sliding windows: Object localization by efficient subwindow search, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.
DOI : 10.1109/CVPR.2008.4587586

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.4517

J. Langford, L. Li, and T. Zhang, Sparse online learning via truncated gradient, In Journal of Machine Learning Research, vol.10, pp.777-801, 2009.

I. Laptev, Improving object detection with boosted histograms, Image and Vision Computing, pp.535-544, 2009.
DOI : 10.1016/j.imavis.2008.08.010

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.4510

S. Lazebnik, C. Schmid, and J. Ponce, Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), pp.2169-2178, 2006.
DOI : 10.1109/CVPR.2006.68

URL : https://hal.archives-ouvertes.fr/inria-00548585

Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner, Gradient-based learning applied to document recognition, Proceedings of the IEEE, pp.2278-2324, 1998.
DOI : 10.1109/5.726791

A. Leibe, B. Leonardis, and . Schiele, An Implicit Shape Model for Combined Object Categorization and Segmentation, Workshop on Statistical Learning in Computer Vision ? ECCV, pp.17-32, 2004.
DOI : 10.1007/11957959_26

B. Leibe, A. Leonardis, and B. Schiele, Robust Object Detection with Interleaved Categorization and Segmentation, International Journal of Computer Vision, vol.73, issue.2, pp.259-289, 2008.
DOI : 10.1007/s11263-007-0095-3

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.111.464

T. Leung and J. Malik, Recognizing surfaces using three-dimensional textons, Proceedings of the Seventh IEEE International Conference on Computer Vision, pp.1010-1017, 1999.
DOI : 10.1109/ICCV.1999.790379

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.7138

Z. Lin and L. S. Davis, A Pose-Invariant Descriptor for Human Detection and Segmentation, Proceedings of the 9th European Conference on Computer Vision, p.83, 2008.
DOI : 10.1007/978-3-540-88693-8_31

Z. Lin, G. Hua, and L. S. Davis, Multiple instance features for robust part-based object detection, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.10-83, 2009.

D. G. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, issue.2, pp.91-110, 2004.
DOI : 10.1023/B:VISI.0000029664.99615.94

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.4931

S. Maji and A. Berg, Max-margin additive classifiers for detection, 2009 IEEE 12th International Conference on Computer Vision, pp.40-47
DOI : 10.1109/ICCV.2009.5459203

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.153.4717

A. Maji, J. Berg, and . Malik, Classification using intersection kernel support vector machines is efficient, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.15-33, 2008.
DOI : 10.1109/CVPR.2008.4587630

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.141.3974

J. Maji and . Malik, Object detection using a max-margin Hough transform, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.1038-1045, 2009.
DOI : 10.1109/CVPR.2009.5206693

K. Mikolajczyk, C. Schmid, and A. Zisserman, Human Detection Based on a Probabilistic Assembly of Robust Part Detectors, Proceedings of the 8th European Conference on Computer Vision, pp.69-81, 2004.
DOI : 10.1007/978-3-540-24670-1_6

URL : https://hal.archives-ouvertes.fr/inria-00548537

C. Mohan, T. Papageorgiou, and . Poggio, Example-based object detection in images by components, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.349-361, 2001.
DOI : 10.1109/34.917571

F. Moosmann, E. Nowak, and F. Jurie, Randomized Clustering Forests for Image Classification, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.1632-1646, 2008.
DOI : 10.1109/TPAMI.2007.70822

URL : https://hal.archives-ouvertes.fr/inria-00548666

F. Moosmann, B. Triggs, and F. Jurie, Fast discriminative visual codebooks using randomized clustering forests, Proceedings of the Neural Information and Processing Systems, pp.985-119, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00203734

T. Ojala, M. Pietikainen, and D. Harwood, A comparative study of texture measures with classification based on featured distributions, Pattern Recognition, vol.29, issue.1, pp.51-59, 1996.
DOI : 10.1016/0031-3203(95)00067-4

T. Ojala, M. Pietikainen, and T. Maenpaa, Multiresolution gray-scale and rotation invariant texture classification with local binary patterns, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.971-987, 2002.
DOI : 10.1109/TPAMI.2002.1017623

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.1576

A. Opelt, A. Pinz, and A. Zisserman, A Boundary-Fragment-Model for Object Detection, Proceedings of the 8th European Conference on Computer Vision, pp.575-588, 2006.
DOI : 10.1007/978-3-540-24671-8_41

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.325.4815

M. Osadchy, Y. L. Cun, and M. Miller, Synergistic Face Detection and Pose Estimation with Energy-Based Models, In Journal of Machine Learning Research, p.16, 2007.
DOI : 10.1007/11957959_10

E. Osuna, R. Freund, and F. Girosi, Training support vector machines: an application to face detection, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.130-136, 1997.
DOI : 10.1109/CVPR.1997.609310

P. Ott and M. Everingham, Implicit color segmentation features for pedestrian and object detection, 2009 IEEE 12th International Conference on Computer Vision, pp.723-730, 2009.
DOI : 10.1109/ICCV.2009.5459238

P. Ott and M. Everingham, Shared parts for deformable part-based models, CVPR 2011, p.12, 2011.
DOI : 10.1109/CVPR.2011.5995357

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.225.6520

C. Papageorgiou and T. Poggio, A trainable system for object detection, International Journal of Computer Vision, vol.38, issue.1, pp.15-33, 2000.
DOI : 10.1023/A:1008162616689

D. Park, D. Ramanan, and C. Fowlkes, Multiresolution Models for Object Detection, Proceedings of the 10th European Conference on Computer Vision, pp.90-112, 2010.
DOI : 10.1007/978-3-642-15561-1_18

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.170.1804

M. Pedersoli, J. Gonzàlez, A. Bagdanov, and J. Villanueva, Recursive Coarse-to-Fine Localization for Fast Object Detection, Proceedings of the 10th European Conference on Computer Vision, pp.280-293, 2010.
DOI : 10.1007/978-3-642-15567-3_21

M. Pedersoli, A. Vedaldi, and J. Gonzàlez, A coarse-to-fine approach for fast deformable object detection, Proceedings of the IEEE Conference on Computer Vision and Pattern

F. Porikli, Integral histogram: a fast way to extract histograms in Cartesian spaces, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.829-836, 2005.
DOI : 10.1109/CVPR.2005.188

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.62.9588

D. Ramanan, Using Segmentation to Verify Object Hypotheses, 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2007.
DOI : 10.1109/CVPR.2007.383271

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.330.1573

M. Ranzato, F. Huang, Y. Boureau, and Y. Lecun, Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition, 2007 IEEE Conference on Computer Vision and Pattern Recognition, p.112, 2007.
DOI : 10.1109/CVPR.2007.383157

J. Razavi and L. V. Gall, Scalable multi-class object detection, CVPR 2011, pp.1505-1512, 2011.
DOI : 10.1109/CVPR.2011.5995441

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.194.1798

R. Ronfard, C. Schmid, and B. Triggs, Learning to Parse Pictures of People, Proceedings of the 7th European Conference on Computer Vision, pp.700-714, 2002.
DOI : 10.1007/3-540-47979-1_47

URL : https://hal.archives-ouvertes.fr/inria-00545109

R. Rosipal and N. Kramer, Overview and Recent Advances in Partial Least Squares, Lecture notes in computer science, pp.34-51, 2006.
DOI : 10.1002/(SICI)1097-0193(1997)5:4<254::AID-HBM9>3.0.CO;2-2

P. Sabzmeydani and G. Mori, Detecting Pedestrians by Learning Shapelet Features, 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2007.
DOI : 10.1109/CVPR.2007.383134

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.205.8978

K. E. Sande, C. G. Gevers, and . Snoek, Evaluating Color Descriptors for Object and Scene Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.9, pp.1582-1596, 2010.
DOI : 10.1109/TPAMI.2009.154

R. Schapire and Y. Singer, Improved boosting algorithms using confidence-rated predictions, Proceedings of the eleventh annual conference on Computational learning theory , COLT' 98, pp.297-336, 1999.
DOI : 10.1145/279943.279960

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.2440

. Schmid, A structured probabilistic model for recognition, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149), pp.485-490, 1999.
DOI : 10.1109/CVPR.1999.784725

URL : https://hal.archives-ouvertes.fr/inria-00548313

H. Schneiderman and T. Kanade, Object Detection Using the Statistics of Parts, International Journal of Computer Vision, vol.56, issue.3, pp.151-177, 2004.
DOI : 10.1023/B:VISI.0000011202.85607.00

P. Schnitzspan, M. Fritz, S. Roth, and B. Schiele, Discriminative structure learning of hierarchical representations for object detection, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.2238-2245, 2009.
DOI : 10.1109/CVPR.2009.5206544

P. Schnitzspan, S. Roth, and B. Schiele, Automatic discovery of meaningful object parts with latent CRFs, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.10-14, 2010.
DOI : 10.1109/CVPR.2010.5540220

B. Schölkopf and A. Smola, Learning with Kernels, p.14, 2002.

A. Schwartz, D. Kembhavi, L. Harwood, and . Davis, Human detection using partial least squares analysis, 2009 IEEE 12th International Conference on Computer Vision, pp.78-83, 2009.
DOI : 10.1109/ICCV.2009.5459205

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.4216

L. Serre, S. Wolf, M. Bileschi, T. Riesenhuber, and . Poggio, Robust Object Recognition with Cortex-Like Mechanisms, Pattern Analysis and Machine Intelligence, pp.411-426, 2007.
DOI : 10.1109/TPAMI.2007.56

URL : http://cbcl.mit.edu/projects/cbcl/publications/ps/serre-wolf-poggio-PAMI-07.pdf

A. Shalev-shwartz and . Tewari, Stochastic methods for L1 regularized loss minimization, Proceedings of the 26th International Conference on Machine learning, pp.929-936, 2009.
DOI : 10.1145/1553374.1553493

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.325.5577

E. Shechtman and M. Irani, Matching Local Self-Similarities across Images and Videos, 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2007.
DOI : 10.1109/CVPR.2007.383198

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.76.1297

J. Shotton, A. Blake, and R. Cipolla, Contour-based learning for object detection, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pp.10-11, 2005.
DOI : 10.1109/ICCV.2005.63

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.159.6494

K. Sung and T. Poggio, Example-based learning for view-based human face detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.1
DOI : 10.1109/34.655648

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.103.3872

X. Tan and B. Triggs, Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions, IEEE Transactions on Image Processing, vol.19, issue.109, pp.1635-1650, 2010.
DOI : 10.1007/978-3-540-75690-3_13

URL : https://hal.archives-ouvertes.fr/inria-00548674

M. Tipping, A. Torralba, K. Murphy, and W. Freeman, Sparse bayesian learning and the relevance vector machine Sharing visual features for multiclass and multiview object detection, Journal, pp.854-869, 2007.

I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun, Large margin methods for structured and interdependent output variables, In Journal of Machine Learning Research, vol.6, issue.2, pp.1453-1478, 2006.

O. Tuzel, F. Porikli, and P. Meer, Region Covariance: A Fast Descriptor for Detection and Classification, Proceedings of the 8th European Conference on Computer Vision, pp.589-600, 2006.
DOI : 10.1023/B:VISI.0000029664.99615.94

O. Tuzel, F. Porikli, and P. Meer, Pedestrian Detection via Classification on Riemannian Manifolds, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.1713-1727, 2008.
DOI : 10.1109/TPAMI.2008.75

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.336.4231

M. Varma and A. Zisserman, Classifying Images of Materials: Achieving Viewpoint and Illumination Independence, Proceedings of the 7th European Conference on Computer Vision, pp.255-271, 2002.
DOI : 10.1007/3-540-47977-5_17

A. Vedaldi, V. Gulshan, M. Varma, and A. Zisserman, Multiple kernels for object detection, 2009 IEEE 12th International Conference on Computer Vision, pp.52-74, 2009.
DOI : 10.1109/ICCV.2009.5459183

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.163.5316

A. Vedaldi and A. Zisserman, Efficient additive kernels via explicit feature maps, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.15-75, 2010.
DOI : 10.1109/cvpr.2010.5539949

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.167.7024

S. Vijayanarasimhan and K. Grauman, Large-scale live active learning: Training object detectors with crawled data and crowds, CVPR 2011, p.113, 2011.
DOI : 10.1109/CVPR.2011.5995430

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.799

P. Viola and M. J. Jones, Robust Real-Time Face Detection, International Journal of Computer Vision, vol.57, issue.2, pp.137-154, 2004.
DOI : 10.1023/B:VISI.0000013087.49260.fb

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.102.9805

. Wandell, Foundations of vision. Sinauer Associates, p.48, 1995.

T. Wang, S. Han, and . Yan, An HOG-LBP human detector with partial occlusion handling, 2009 IEEE 12th International Conference on Computer Vision, pp.43-83, 2009.
DOI : 10.1109/ICCV.2009.5459207

S. Wold, M. Sjöström, and L. Eriksson, PLS-regression: a basic tool of chemometrics, Chemometrics and Intelligent Laboratory Systems, pp.109-130, 2001.
DOI : 10.1016/S0169-7439(01)00155-1

B. Wu and R. Nevatia, Detection and Tracking of Multiple, Partially Occluded Humans by Bayesian Combination of Edgelet based Part Detectors, International Journal of Computer Vision, vol.I, issue.4, pp.247-266, 2007.
DOI : 10.1007/s11263-006-0027-7

B. Wu and R. Nevatia, Optimizing discrimination-efficiency tradeoff in integrating heterogeneous local features for object detection, Proceedings of the 9th European Conference on Computer Vision, pp.83-85, 2008.

B. Wu and R. Nevatia, Detection and Segmentation of Multiple, Partially Occluded Objects by Grouping, Merging, Assigning Part Detection Responses, International Journal of Computer Vision, vol.75, issue.2, pp.185-204, 2009.
DOI : 10.1007/s11263-008-0194-9

H. Yu, F. Huang, and C. Lin, Dual coordinate descent methods for logistic regression and maximum entropy models, Machine Learning, vol.46, issue.1???3, pp.1-35, 2011.
DOI : 10.1007/s10994-010-5221-8

Y. Yu, J. Zhang, Y. Huang, S. Zheng, W. Ren et al., Object detection by context and boosted HOG-LBP, pp.104-112, 2010.

J. Zhang, K. Huang, Y. Yu, and T. Tan, Boosted local structured HOG-LBP for object localization, CVPR 2011, pp.1393-1400, 2011.
DOI : 10.1109/CVPR.2011.5995678

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.362.6498

C. Zheng, X. Shen, and . Huang, Pedestrian detection using center-symmetric local binary patterns, Proceedings of the IEEE International Conference on Image Processing, pp.47-54, 2010.

J. Zhu, A. Ahmed, and E. Xing, MedLDA, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, pp.1257-1264, 2009.
DOI : 10.1145/1553374.1553535

L. Zhu, Y. Chen, A. Yuille, and W. Freeman, Latent hierarchical structural learning for object detection, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.11-112, 2010.

Q. Zhu, S. Avidan, M. Ye, and K. Cheng, Fast human detection using a cascade of histograms of oriented gradients, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.11-18, 2006.