Sparsity-driven people localization algorithm: Evaluation in crowded scenes environments, 2009 Twelfth IEEE International Workshop on Performance Evaluation of Tracking and Surveillance, 2009. ,
DOI : 10.1109/PETS-WINTER.2009.5399487
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.162.1226
Multi camera person tracking applying a graph-cuts based foreground segmentation in a homography framework, 2009 Twelfth IEEE International Workshop on Performance Evaluation of Tracking and Surveillance, 2009. ,
DOI : 10.1109/PETS-WINTER.2009.5399723
Part-Based Feature Synthesis for Human Detection, 2010. ,
DOI : 10.1007/978-3-642-15561-1_10
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.178.9368
Pedestrian detection at 100 frames per second, 2012 IEEE Conference on Computer Vision and Pattern Recognition, p.2012 ,
DOI : 10.1109/CVPR.2012.6248017
Pedestrian detection at 100 frames per second, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2013. ,
DOI : 10.1109/CVPR.2012.6248017
Ten years of pedestrian detection, what have we learned? ECCV, CVRSUAD workshop, 2014. ,
DOI : 10.1007/978-3-319-16181-5_47
URL : http://arxiv.org/abs/1411.4304
Fast human detection with cascaded ensembles on the gpu, IEEE Intelligent Vehicles Symposium, 2010. ,
Pedestrian detection in infrared images, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683), 2003. ,
DOI : 10.1109/IVS.2003.1212991
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.74.2821
Poselets: Body part detectors trained using 3d human pose annotations [11] L. Breiman. Random forests Markovian tracking-by-detection from a single, Machine Learning, pp.71-78, 2001. ,
DOI : 10.1109/iccv.2009.5459303
Non-maximum suppression, 2011. ,
Detection Evolution with Multi-order Contextual Co-occurrence, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013. ,
DOI : 10.1109/CVPR.2013.235
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.308.6409
Performance evaluation of a people tracking system on the pets video database, 2009. ,
Haar like and lbp based features for face, head and people detection in video sequences, ICVS, 2011. ,
URL : https://hal.archives-ouvertes.fr/inria-00624360
Word Channel Based Multiscale Pedestrian Detection without Image Resizing and Using Only One Classifier, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014. ,
DOI : 10.1109/CVPR.2014.307
Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005. ,
DOI : 10.1109/CVPR.2005.177
URL : https://hal.archives-ouvertes.fr/inria-00548512
The Fastest Pedestrian Detector in the West, Procedings of the British Machine Vision Conference 2010, 2010. ,
DOI : 10.5244/C.24.68
Integral Channel Features, Procedings of the British Machine Vision Conference 2009, 2009. ,
DOI : 10.5244/C.23.91
URL : http://authors.library.caltech.edu/60048/1/dollarBMVC09ChnFtrs.pdf
Pedestrian detection: A benchmark, 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009. ,
DOI : 10.1109/CVPR.2009.5206631
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.212.258
Pedestrian Detection: An Evaluation of the State of the Art, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.4, 2012. ,
DOI : 10.1109/TPAMI.2011.155
Crosstalk cascades for frame-rate pedestrian detection, p.2012 ,
The fastest pedestrian detector in the west, BMVC, 2010. ,
Pedestrian detection: A benchmark, 2009. ,
The foundations of cost-sensitive learning. Intl Joint Conf, Artificial Intelligence, 2001. ,
PETS2010 and PETS2009 Evaluation of Results Using Individual Ground Truthed Single Views, 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance, 2010. ,
DOI : 10.1109/AVSS.2010.89
Comparison between infrared-imagebased and visible-image-based approaches for pedestrian detection, IEEE, 2003. ,
DOI : 10.1109/ivs.2003.1212963
A discriminatively trained, multiscale, deformable part model, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008. ,
DOI : 10.1109/CVPR.2008.4587597
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.686
Cascade object detection with deformable part models, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010. ,
DOI : 10.1109/CVPR.2010.5539906
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.164.8688
Object Detection with Discriminatively Trained Part-Based Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.9, pp.1627-1645, 2009. ,
DOI : 10.1109/TPAMI.2009.167
An overview of the pets2009 challenge, 2009. ,
Class-specific hough forests for object detection, 2009. ,
DOI : 10.1109/cvprw.2009.5206740
Context based object categorization: A critical survey, Computer Vision and Image Understanding, vol.114, issue.6, pp.712-722, 2010. ,
DOI : 10.1016/j.cviu.2010.02.004
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.933
Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning, Intl Conf. Intelligent Computing, 2005. ,
DOI : 10.1007/11538059_91
Adasyn: Adaptive synthetic sampling approach for imbalanced learning, Intl J. Conf. Neural Networks, 2008. ,
Learning from imbalanced data, IEEE transactions on Knowledge and data engineering, vol.21, issue.9, 2009. ,
Putting objects in perspective, IJVC, 2008. ,
DOI : 10.1109/cvpr.2006.232
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.141.6201
A Two Phase Approach for Pedestrian Detection, ACCV, 2014. ,
DOI : 10.1007/978-3-319-16631-5_34
Learning from imbalanced data sets: a comparison of various strategies, AAAI Workshop on Learning from Imbalanced Data Sets, 2000. ,
Class imbalances versus small disjuncts, ACM SIGKDD Explorations Newsletter, vol.6, issue.1, pp.40-49, 2004. ,
DOI : 10.1145/1007730.1007737
Pedestrian detection via PCA filters based convolutional channel features, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015. ,
DOI : 10.1109/ICASSP.2015.7178199
Multi-channel correlation filters for human action recognition, 2014 IEEE International Conference on Image Processing (ICIP), 2014. ,
DOI : 10.1109/ICIP.2014.7025297
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.570.1662
Random Forests of Local Experts for Pedestrian Detection, 2013 IEEE International Conference on Computer Vision, 2013. ,
DOI : 10.1109/ICCV.2013.322
Local decorrelation for improved pedestrian detection, NIPS, 2014. ,
Local decorrelation for improved pedestrian detection, NIPS, 2014. ,
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.7, 2002. ,
DOI : 10.1109/TPAMI.2002.1017623
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.1576
Joint Deep Learning for Pedestrian Detection, 2013 IEEE International Conference on Computer Vision, 2013. ,
DOI : 10.1109/ICCV.2013.257
Joint Deep Learning for Pedestrian Detection, 2013 IEEE International Conference on Computer Vision, 2013. ,
DOI : 10.1109/ICCV.2013.257
Single-Pedestrian Detection Aided by Multi-pedestrian Detection, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013. ,
DOI : 10.1109/CVPR.2013.411
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.644.5337
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
Robust real-time face detection. IJCV, 2004. ,
Multiresolution Models for Object Detection, 2010. ,
DOI : 10.1007/978-3-642-15561-1_18
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.170.1804
Exploring Weak Stabilization for Motion Feature Extraction, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013. ,
DOI : 10.1109/CVPR.2013.371
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.294.4829
Persistent Tracking for Wide Area Aerial Surveillance, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014. ,
DOI : 10.1109/CVPR.2014.155
Local Context Priors for Object Proposal Generation, 2012. ,
DOI : 10.1007/978-3-642-37331-2_5
URL : https://lirias.kuleuven.be/bitstream/123456789/377379/1/3559_postprint.pdf
Local Response Context Applied to Pedestrian Detection, CIARP, 2011. ,
DOI : 10.1109/ICCV.2007.4409057
Optimized cascade of classifiers for people detection using covariance features, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00794369
An instance-weighting method to induce cost-sensitive trees, IEEE Transactions on Knowledge and Data Engineering, vol.14, issue.3, pp.659-665, 2002. ,
DOI : 10.1109/TKDE.2002.1000348
Two modifications of cnn, IEEE Trans. System, Man, Cybernetics, issue.611, pp.769-772, 1976. ,
Rapid object detection using a boosted cascade of simple features, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001. ,
DOI : 10.1109/CVPR.2001.990517
New features and insights for pedestrian detection, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010. ,
DOI : 10.1109/CVPR.2010.5540102
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.294.7144
Imbalanced data set learning with synthetic samples, IRIS Machine Learning Workshop, 2004. ,
An HOG-LBP human detector with partial occlusion handling, 2009 IEEE 12th International Conference on Computer Vision, 2009. ,
DOI : 10.1109/ICCV.2009.5459207
A sparse probabilistic learning algorithm for real-time tracking, Proceedings Ninth IEEE International Conference on Computer Vision, 2003. ,
DOI : 10.1109/ICCV.2003.1238366
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.4.1984
A performance evaluation of single and multi-feature people detection. DAGM Symposium Pattern Recognition, 2008. ,
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
A decision-theoric generalization of online learning and an application to boosting, Journal of Computer and System Sciences, 1997. ,
Robust Multi-resolution Pedestrian Detection in Traffic Scenes, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013. ,
DOI : 10.1109/CVPR.2013.390
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.679.797
On predicting rare classes with svm ensemble in scene classification, ICASSP, 2003. ,
Probabilistic multiple people tracking through complex situations, 2009. ,
Informed Haar-Like Features Improve Pedestrian Detection, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014. ,
DOI : 10.1109/CVPR.2014.126
Fast human detection using a cascade of histograms of oriented gradients, 2006. ,