C. Keller, M. Enzweiler, M. Rohrbach, D. Llorca, C. Schnorr et al., The Benefits of Dense Stereo for Pedestrian Detection, IEEE Transactions on Intelligent Transportation Systems, vol.12, issue.4, pp.1096-1106, 2011.
DOI : 10.1109/TITS.2011.2143410

D. Gavrila and S. Munder, Multi-cue Pedestrian Detection and Tracking from a Moving Vehicle, International Journal of Computer Vision, vol.10, issue.6, pp.41-59, 2007.
DOI : 10.1007/s11263-006-9038-7

Z. Sun, G. Bebis, and R. Miller, On-road vehicle detection: A review, IEEE Trans. Pattern Anal. Mach. Intell, vol.28, issue.5, pp.694-711, 2006.

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

P. Dollar, C. Wojek, B. Schiele, and P. Perona, Pedestrian Detection: An Evaluation of the State of the Art, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.4, pp.743-761, 2012.
DOI : 10.1109/TPAMI.2011.155

M. Enzweiler and D. Gavrila, Monocular Pedestrian Detection: Survey and Experiments, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.12, pp.2179-2195, 2009.
DOI : 10.1109/TPAMI.2008.260

M. Enzweiler and D. Gavrila, A Multilevel Mixture-of-Experts Framework for Pedestrian Classification, IEEE Transactions on Image Processing, vol.20, issue.10, pp.2967-2979, 2011.
DOI : 10.1109/TIP.2011.2142006

B. Dalal and N. 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

M. Awais and K. Mikolajczyk, Feature Pairs Connected by Lines for Object Recognition, 2010 20th International Conference on Pattern Recognition, pp.3093-3096, 2010.
DOI : 10.1109/ICPR.2010.757

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.370.6947

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.1-3, 2008.
DOI : 10.1007/s11263-007-0095-3

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

E. Seemann, M. Fritz, and B. Schiele, Towards Robust Pedestrian Detection in Crowded Image Sequences, 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2007.
DOI : 10.1109/CVPR.2007.383300

P. F. Felzenszwalb, R. B. Girshick, D. A. Mcallester, and D. Ramanan, Object Detection with Discriminatively Trained Part-Based Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.9, pp.1627-1645, 2010.
DOI : 10.1109/TPAMI.2009.167

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

J. Gall and V. S. Lempitsky, Class-Specific Hough Forests for Object Detection, Proc. IEEE Conf. CVPR, pp.1022-1029, 2009.
DOI : 10.1007/978-1-4471-4929-3_11

A. Opelt, A. Pinz, and A. Zisserman, Learning an Alphabet of Shape and Appearance for Multi-Class Object Detection, International Journal of Computer Vision, vol.73, issue.2, pp.16-44, 2008.
DOI : 10.1007/s11263-008-0139-3

R. Labayrade, D. Aubert, and J. Tarel, Real time obstacle detection in stereovision on non flat road geometry through "v-disparity" representation, Intelligent Vehicle Symposium, 2002. IEEE, pp.646-651, 2002.
DOI : 10.1109/IVS.2002.1188024

A. Broggi, C. Caraffi, P. Porta, and P. Zani, The Single Frame Stereo Vision System for Reliable Obstacle Detection Used during the 2005 DARPA Grand Challenge on TerraMax, 2006 IEEE Intelligent Transportation Systems Conference, pp.745-752, 2006.
DOI : 10.1109/ITSC.2006.1706831

G. Toulminet, M. Bertozzi, S. Mousset, A. Bensrhair, and A. Broggi, Vehicle detection by means of stereo vision-based obstacles features extraction and monocular pattern analysis, IEEE Transactions on Image Processing, vol.15, issue.8, pp.2364-2375, 2006.
DOI : 10.1109/TIP.2006.875174

URL : https://hal.archives-ouvertes.fr/hal-00478467

T. Veit, Connexity based fronto-parallel plane detection for stereovision obstacle segmentation, Proc, pp.1-15, 2009.

B. Leibe, K. Schindler, N. Cornelis, and L. J. , Coupled Object Detection and Tracking from Static Cameras and Moving Vehicles, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.10, pp.1683-1698, 2008.
DOI : 10.1109/TPAMI.2008.170

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.145.9138

I. P. Alonso, D. F. Llorca, M. Á. Sotelo, L. M. Bergasa, P. R. De-toro et al., Combination of Feature Extraction Methods for SVM Pedestrian Detection, IEEE Transactions on Intelligent Transportation Systems, vol.8, issue.2, pp.292-307, 2007.
DOI : 10.1109/TITS.2007.894194

R. Quintero, A. Llamazares, D. Llorca, M. Sotelo, L. Bellot et al., Extended Floating Car Data system - experimental study, 2011 IEEE Intelligent Vehicles Symposium (IV), pp.631-636, 2011.
DOI : 10.1109/IVS.2011.5940444

J. V. Diaz, D. Fernandez-llorca, A. Rodriguez-gonzalez, R. Quintero-minguez, A. Llamazares et al., Extended Floating Car Data System: Experimental Results and Application for a Hybrid Route Level of Service, IEEE Transactions on Intelligent Transportation Systems, vol.13, issue.1, pp.25-35, 2012.
DOI : 10.1109/TITS.2011.2178834

C. Burges, A tutorial on support vector machines for pattern recognition, Data Mining and Knowledge Discovery, vol.2, issue.2, pp.121-167, 1998.
DOI : 10.1023/A:1009715923555

M. Enzweiler, M. Hummel, D. Pfeiffer, and U. Franke, Efficient stixelbased object recognition, Proc. IEEE IV, pp.1066-1071, 2012.

D. Geronimo, A. D. Sappa, A. Lopez, and D. Ponsa, Adaptive image sampling and windows classification for on-board pedestrian detection, Proc. 5th Int. Conf. Comput. Vis. Syst, pp.21-24, 2007.

A. Makris, M. Perrollaz, I. Paromtchik, and C. Laugier, Integration of visual and depth information for vehicle detection, Proc. IEEE/RSJ IROS, Workshop Perception Navigat. Auton. Veh. Human Environ, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00683755

R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2000.
DOI : 10.1017/CBO9780511811685

H. Hirschmüller, Stereo Processing by Semiglobal Matching and Mutual Information, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.2, pp.328-341, 2008.
DOI : 10.1109/TPAMI.2007.1166

M. Perrollaz, J. Yoder, A. Nègre, A. Spalanzani, and C. Laugier, A Visibility-Based Approach for Occupancy Grid Computation in Disparity Space, IEEE Transactions on Intelligent Transportation Systems, vol.13, issue.3, pp.1383-1393, 2012.
DOI : 10.1109/TITS.2012.2188393

URL : https://hal.archives-ouvertes.fr/hal-00671208

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

R. B. Girshick, P. F. Felzenszwalb, and D. Mcallester, Discriminatively trained deformable part models, release 5

J. Ponce, T. L. Berg, M. Everingham, D. A. Forsyth, M. Hebert et al., Dataset Issues in Object Recognition, Toward Category-Level Object Recognition, pp.29-48, 2006.
DOI : 10.1007/11957959_2

URL : https://hal.archives-ouvertes.fr/inria-00548595