Age classification for pose variant and occluded faces

Authors:
Wei-Ta Chu;Wen-Long Liu;Jen-Yu Yu
Affiliations:
National Chung Cheng University, Chiayi, Taiwan Roc;National Chung Cheng University, Chiayi, Taiwan Roc;Industrial Technology Research Inst., Hsinchu, Taiwan Roc
Venue:
Proceedings of the international conference on Multimedia
Year:
2010

Citing 9
Cited 1

Age classification from facial images

Computer Vision and Image Understanding
Selection of Scale-Invariant Parts for Object Class Recognition

ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
Automatic Age Estimation Based on Facial Aging Patterns

IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational methods for modeling facial aging: A survey

Journal of Visual Languages and Computing
Detection, Localization, and Sex Classification of Faces from Arbitrary Viewpoints and under Occlusion

IEEE Transactions on Pattern Analysis and Machine Intelligence
Web image mining towards universal age estimator

MM '09 Proceedings of the 17th ACM international conference on Multimedia
Classification of face images for gender, age, facial expression, and identity

ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Human Age Estimation With Regression on Discriminative Aging Manifold

IEEE Transactions on Multimedia

Bilinear deep learning for image classification

MM '11 Proceedings of the 19th ACM international conference on Multimedia

Quantified Score

Hi-index	0.00

Visualization

Abstract

We extend the object class invariant (OCI) model to age classification, for pose variant and occluded faces. With the OCI model, we first localize faces from images captured in arbitrary views, and then determine the most distinctive features. Relationships between feature points and the invariant vector are described in terms of geometry and appearance information, in the form of a probabilistic model. In contrast to previous works on age classification/estimation, we emphasize that this method is especially useful for faces captured in real-world situations.