A Survey of Recent Advances in Face Detection

Face detection has been one of the most studied topics in the computer vision literature. In this technical report, we survey the recent advances in face detection for the past decade. The seminal Viola-Jones face detector is first reviewed. We then survey the various techniques according to how they extract features and what learning algorithms are adopted. It is our hope that by reviewing the many existing algorithms, we will see even better algorithms developed to solve this fundamental computer vision problem. 1

[1]  J. Andel.  Sequential Analysis , 2022, The SAGE Encyclopedia of Research Design.

[2]  David G. Stork,et al.  Pattern Classification , 1973 .

[3]  Franklin C. Crow,et al.  Summed-area tables for texture mapping , 1984, SIGGRAPH.

[4]  Josef Kittler,et al.  Floating search methods in feature selection , 1994, Pattern Recognit. Lett..

[5]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.

[6]  Federico Girosi,et al.  Training support vector machines: an application to face detection , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[7]  Takeo Kanade,et al.  Rotation invariant neural network-based face detection , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[8]  Takeo Kanade,et al.  Neural Network-Based Face Detection , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Yoram Singer,et al.  Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.

[10]  Narendra Ahuja,et al.  A SNoW-Based Face Detector , 1999, NIPS.

[11]  Peter L. Bartlett,et al.  Boosting Algorithms as Gradient Descent , 1999, NIPS.

[12]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[13]  J. Friedman.  Special Invited Paper-Additive logistic regression: A statistical view of boosting , 2000 .

[14]  Massimiliano Pontil,et al.  Face Detection in Still Gray Images , 2000 .

[15]  Shaogang Gong,et al.  Support vector regression and classification based multi-view face detection and recognition , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[16]  Gail A. Carpenter,et al.  S-TREE: self-organizing trees for data clustering and online vector quantization , 2001, Neural Networks.

[17]  Tomaso A. Poggio,et al.  Example-Based Object Detection in Images by Components , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Stan Z. Li,et al.  Learning representative local features for face detection , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[19]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.

[20]  Daniel Keren,et al.  Antifaces: A Novel, Fast Method for Image Detection , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Erik Hjelmås,et al.  Face Detection: A Survey , 2001, Comput. Vis. Image Underst..

[22]  Paul A. Viola,et al.  Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade , 2001, NIPS.

[23]  Andrew Blake,et al.  Computationally efficient face detection , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[24]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[25]  Raphaël Féraud,et al.  A Fast and Accurate Face Detector Based on Neural Networks , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Stanley M. Bileschi,et al.  Advances in Component-Based Face Detection , 2002, SVM.

[27]  Harry Shum,et al.  Statistical Learning of Multi-view Face Detection , 2002, ECCV.

[28]  Gunnar Rätsch,et al.  An Introduction to Boosting and Leveraging , 2002, Machine Learning Summer School.

[29]  Rainer Lienhart,et al.  An extended set of Haar-like features for rapid object detection , 2002, Proceedings. International Conference on Image Processing.

[30]  Narendra Ahuja,et al.  Detecting Faces in Images: A Survey , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[31]  Matti Pietikäinen,et al.  Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[32]  Brendan McCane,et al.  On Training Cascade Face Detectors , 2003 .

[33]  Chengjun Liu,et al.  A Bayesian Discriminating Features Method for Face Detection , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  James M. Rehg,et al.  Learning a Rare Event Detection Cascade by Direct Feature Selection , 2003, NIPS.

[35]  J. Wade Davis,et al.  Statistical Pattern Recognition , 2003, Technometrics.

[36]  Thomas Serre,et al.  Hierarchical classification and feature reduction for fast face detection with support vector machines , 2003, Pattern Recognit..

[37]  Paul A. Viola,et al.  Fast Multi-view Face Detection , 2003 .

[38]  Harry Shum,et al.  Kullback-Leibler boosting , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[39]  Rainer Lienhart,et al.  Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection , 2003, DAGM-Symposium.

[40]  Andreas Ernst,et al.  Fast Frontal-View Face Detection Using a Multi-path Decision Tree , 2003, AVBPA.

[41]  Rong Xiao,et al.  Boosting chain learning for object detection , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[42]  B. Schiele,et al.  Fast and Robust Face Finding via Local Context , 2003 .

[43]  Qiang Ji,et al.  Multi-view face detection under complex scene based on combined SVMs , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[44]  Gunnar Rätsch,et al.  Advanced Lectures on Machine Learning , 2004, Lecture Notes in Computer Science.

[45]  Andreas Ernst,et al.  Face detection with the modified census transform , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[46]  Henry Schneiderman,et al.  Learning a restricted Bayesian network for object detection , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[47]  Yair Weiss,et al.  Learning object detection from a small number of examples: the importance of good features , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[48]  Takeo Kanade,et al.  Object Detection Using the Statistics of Parts , 2004, International Journal of Computer Vision.

[49]  A. Torralba,et al.  Sharing features: efficient boosting procedures for multiclass object detection , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[50]  Xihong Wu,et al.  Boosting Local Binary Pattern (LBP)-Based Face Recognition , 2004, SINOBIOMETRICS.

[51]  Christophe Garcia,et al.  Convolutional face finder: a neural architecture for fast and robust face detection , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[52]  Yann LeCun,et al.  Synergistic Face Detection and Pose Estimation with Energy-Based Models , 2004, J. Mach. Learn. Res..

[53]  Bo Wu,et al.  Fast rotation invariant multi-view face detection based on real Adaboost , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[54]  Hanqing Lu,et al.  Face detection using improved LBP under Bayesian framework , 2004, Third International Conference on Image and Graphics (ICIG'04).

[55]  H. Schneiderman.  Feature-centric evaluation for efficient cascaded object detection , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[56]  Bruno Steux,et al.  YEF∗Real-Time Object Detection , 2004 .

[57]  Shumeet Baluja,et al.  Efficient face orientation discrimination , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[58]  Sami Romdhani,et al.  Efficient Face Detection by a Cascaded Support Vector Machine Using Haar-Like Features , 2004, DAGM-Symposium.

[59]  Cordelia Schmid,et al.  Human Detection Based on a Probabilistic Assembly of Robust Part Detectors , 2004, ECCV.

[60]  Huitao Luo,et al.  Optimization design of cascaded classifiers , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[61]  Bernt Schiele,et al.  Pedestrian detection in crowded scenes , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[62]  Qiang Ji,et al.  Learning discriminant features for multi-view face and eye detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[63]  Xiuwen Liu,et al.  Face detection using spectral histograms and SVMs , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[64]  Zhuowen Tu,et al.  Probabilistic boosting-tree: learning discriminative models for classification, recognition, and clustering , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[65]  Jiri Matas,et al.  WaldBoost - learning for time constrained sequential detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[66]  Takeshi Mita,et al.  Joint Haar-like features for face detection , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[67]  Paul A. Viola,et al.  Detecting Pedestrians Using Patterns of Motion and Appearance , 2005, International Journal of Computer Vision.

[68]  Minh-Tri Pham,et al.  Detection Caching for Faster Object Detection , 2005 .

[69]  Paul A. Viola,et al.  Multiple Instance Boosting for Object Detection , 2005, NIPS.

[70]  Andrew Blake,et al.  Contour-based learning for object detection , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[71]  Jonathan Brandt,et al.  Robust object detection via soft cascade , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[72]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[73]  Ramakant Nevatia,et al.  Detection of multiple, partially occluded humans in a single image by Bayesian combination of edgelet part detectors , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[74]  Yuan Li,et al.  Vector boosting for rotation invariant multi-view face detection , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[75]  Fatih Murat Porikli,et al.  Integral histogram: a fast way to extract histograms in Cartesian spaces , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[76]  Tyng-Luh Liu,et al.  Robust face detection with multi-class boosting , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[77]  Mei-Chen Yeh,et al.  Fast Human Detection Using a Cascade of Histograms of Oriented Gradients , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[78]  Horst Bischof,et al.  On-line Boosting and Vision , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[79]  Wen Gao,et al.  Object detection using spatial histogram features , 2006, Image Vis. Comput..

[80]  Andrew Zisserman,et al.  A Boundary-Fragment-Model for Object Detection , 2006, ECCV.

[81]  Feng Han,et al.  Learning Exemplar-Based Categorization for the Detection of Multi-View Multi-Pose Objects , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[82]  Yuan Li,et al.  Learning sparse features in granular space for multi-view face detection , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[83]  A. Broggi,et al.  Pedestrian Detection using Infrared images and Histograms of Oriented Gradients , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[84]  Thomas Serre,et al.  A Component-based Framework for Face Detection and Identification , 2007, International Journal of Computer Vision.

[85]  Bernt Schiele,et al.  Multi-Aspect Detection of Articulated Objects , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[86]  Ivan Laptev,et al.  Improvements of Object Detection Using Boosted Histograms , 2006, BMVC.

[87]  Fatih Murat Porikli,et al.  Region Covariance: A Fast Descriptor for Detection and Classification , 2006, ECCV.

[88]  Shengcai Liao,et al.  Face Detection Based on Multi-Block LBP Representation , 2007, ICB.

[89]  Ting Yu,et al.  Gradient Feature Selection for Online Boosting , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[90]  B. K. Julsing,et al.  Face Recognition with Local Binary Patterns , 2012 .

[91]  Jean-Philippe Thiran,et al.  Face detection with boosted Gaussian features , 2007, Pattern Recognit..

[92]  Ramakant Nevatia,et al.  Cluster Boosted Tree Classifier for Multi-View, Multi-Pose Object Detection , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[93]  R. Nevatia,et al.  Simultaneous Object Detection and Segmentation by Boosting Local Shape Feature based Classifier , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[94]  Michael C. Nechyba,et al.  PittPatt Face Detection and Tracking for the CLEAR 2007 Evaluation , 2007, CLEAR.

[95]  Rong Xiao,et al.  Dynamic Cascades for Face Detection , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[96]  Tat-Jen Cham,et al.  Online Learning Asymmetric Boosted Classifiers for Object Detection , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[97]  Paul A. Viola,et al.  Multiple-Instance Pruning For Learning Efficient Cascade Detectors , 2007, NIPS.

[98]  Kazuhiro Hotta,et al.  View Independent Face Detection Based on Combination of Local and Global Kernels , 2007, ICVS 2007.

[99]  Greg Mori,et al.  Detecting Pedestrians by Learning Shapelet Features , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[100]  James M. Rehg,et al.  On the Design of Cascades of Boosted Ensembles for Face Detection , 2008, International Journal of Computer Vision.

[101]  Jie Yan.  Ensemble SVM Regression Based Multi-View Face Detection System , 2007, 2007 IEEE Workshop on Machine Learning for Signal Processing.

[102]  Nuno Vasconcelos,et al.  Asymmetric boosting , 2007, ICML '07.

[103]  Tat-Jen Cham,et al.  Fast training and selection of Haar features using statistics in boosting-based face detection , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[104]  Takayoshi Yamashita,et al.  Incremental Learning of Boosted Face Detector , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[105]  Nuno Vasconcelos,et al.  High Detection-rate Cascades for Real-Time Object Detection , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[106]  James M. Rehg,et al.  Fast Asymmetric Learning for Cascade Face Detection , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[107]  Feng Han,et al.  Discovering class specific composite features through discriminative sampling with Swendsen-Wang Cut , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[108]  Jiebo Luo,et al.  Mining compositional features for boosting , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[109]  Serge J. Belongie,et al.  Simultaneous Learning and Alignment: Multi-Instance and Multi-Pose Learning ? , 2008 .

[110]  Wen Gao,et al.  Locally Assembled Binary (LAB) feature with feature-centric cascade for fast and accurate face detection , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[111]  Roberto Cipolla,et al.  MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features , 2008, NIPS.

[112]  Jong-Hwan Kim,et al.  Fast and Robust Face Detection Using Evolutionary Pruning , 2008, IEEE Transactions on Evolutionary Computation.

[113]  Zhengyou Zhang,et al.  Taylor expansion based classifier adaptation: Application to person detection , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[114]  Wei Gao,et al.  Adaptive Contour Features in oriented granular space for human detection and segmentation , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[115]  Dariu Gavrila,et al.  Monocular Pedestrian Detection: Survey and Experiments , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[116]  Zhengyou Zhang,et al.  Winner-Take-All Multiple Category Boosting for Multi-view Face Detection , 2009 .

[117]  Shuicheng Yan,et al.  An HOG-LBP human detector with partial occlusion handling , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[118]  Gang Hua,et al.  Context-Aware Visual Tracking , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[119]  Serge J. Belongie,et al.  Context based object categorization: A critical survey , 2010, Comput. Vis. Image Underst..

[120]  Erik Learned-Miller,et al.  FDDB: A benchmark for face detection in unconstrained settings , 2010 .