Apparent and Real Age Estimation in Still Images with Deep Residual Regressors on Appa-Real Database

After decades of research, the real (biological) age estimation from a single face image reached maturity thanks to the availability of large public face databases and impressive accuracies achieved by recently proposed methods. The estimation of “apparent age” is a related task concerning the age perceived by human observers. Significant advances have been also made in this new research direction with the recent Looking At People challenges. In this paper we make several contributions to age estimation research. (i) We introduce APPA-REAL, a large face image database with both real and apparent age annotations. (ii)We study the relationship between real and apparent age. (iii) We develop a residual age regression method to further improve the performance. (iv) We show that real age estimation can be successfully tackled as an apparent age estimation followed by an apparent to real age residual regression. (v) We graphically reveal the facial regions on which the CNN focuses in order to perform apparent and real age estimation tasks.

[1]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[2]  Sergio Escalera,et al.  ChaLearn Looking at People 2015: Apparent Age and Cultural Event Recognition Datasets and Results , 2015, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW).

[3]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[4]  Shaogang Gong,et al.  Cumulative Attribute Space for Age and Crowd Density Estimation , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[5]  Bingbing Ni,et al.  Web image mining towards universal age estimator , 2009, ACM Multimedia.

[6]  Yun Fu,et al.  Human Age Estimation With Regression on Discriminative Aging Manifold , 2008, IEEE Transactions on Multimedia.

[7]  Changsheng Li,et al.  Learning ordinal discriminative features for age estimation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Luc Van Gool,et al.  Structured Output SVM Prediction of Apparent Age, Gender and Smile from Deep Features , 2016, CVPR 2016.

[9]  Denise C. Park,et al.  A lifespan database of adult facial stimuli , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[10]  Terence Sim,et al.  The CMU Pose, Illumination, and Expression (PIE) database , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[11]  Yun Fu,et al.  Age Synthesis and Estimation via Faces: A Survey , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  D. Perrett,et al.  Perception of age in adult Caucasian male faces: computer graphic manipulation of shape and colour information , 1995, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[13]  Rama Chellappa,et al.  Computational methods for modeling facial aging: A survey , 2009, J. Vis. Lang. Comput..

[14]  Harry Wechsler,et al.  The FERET database and evaluation procedure for face-recognition algorithms , 1998, Image Vis. Comput..

[15]  Anil K. Jain,et al.  Age estimation from face images: Human vs. machine performance , 2013, 2013 International Conference on Biometrics (ICB).

[16]  Tetsunori Kobayashi,et al.  Subspace-based age-group classification using facial images under various lighting conditions , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[17]  Wei Zhang,et al.  Deeply Learned Rich Coding for Cross-Dataset Facial Age Estimation , 2015, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW).

[18]  Jean-Luc Dugelay,et al.  Apparent Age Estimation from Face Images Combining General and Children-Specialized Deep Learning Models , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[19]  Luc Van Gool,et al.  Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks , 2016, International Journal of Computer Vision.

[20]  Yan Li,et al.  A Study on Apparent Age Estimation , 2015, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW).

[21]  Patrick J. Flynn,et al.  Overview of the face recognition grand challenge , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[22]  Zhi-Hua Zhou,et al.  Facial Age Estimation by Learning from Label Distributions , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  Andrew C. Gallagher,et al.  Understanding images of groups of people , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[24]  Mohammad Mahdi Dehshibi,et al.  Iranian Face Database with age, pose and expression , 2007, 2007 International Conference on Machine Vision.

[25]  Karl Ricanek,et al.  MORPH: a longitudinal image database of normal adult age-progression , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[26]  Tal Hassner,et al.  Age and Gender Estimation of Unfiltered Faces , 2014, IEEE Transactions on Information Forensics and Security.

[27]  Shiguang Shan,et al.  Coarse-to-Fine Auto-Encoder Networks (CFAN) for Real-Time Face Alignment , 2014, ECCV.

[28]  Andrew Zisserman,et al.  Deep Face Recognition , 2015, BMVC.

[29]  Sangseung Kang,et al.  Human age estimation using multi-class SVM , 2015, 2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI).

[30]  Xu Yang,et al.  Deep Age Distribution Learning for Apparent Age Estimation , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[31]  Jun Wan,et al.  DFDnet: Discriminant Face Descriptor Network for Facial Age Estimation , 2015, CCBR.

[32]  Timothy F. Cootes,et al.  Toward Automatic Simulation of Aging Effects on Face Images , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[33]  Luc Van Gool,et al.  DEX: Deep EXpectation of Apparent Age from a Single Image , 2015, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW).

[34]  Rama Chellappa,et al.  A hierarchical approach for human age estimation , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[35]  Xin Liu,et al.  AgeNet: Deeply Learned Regressor and Classifier for Robust Apparent Age Estimation , 2015, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW).

[36]  Tal Hassner,et al.  Age and gender classification using convolutional neural networks , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[37]  Luc Van Gool,et al.  Face Detection without Bells and Whistles , 2014, ECCV.

[38]  Sergio Escalera,et al.  ChaLearn Looking at People and Faces of the World: Face AnalysisWorkshop and Challenge 2016 , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).