Toward Automatic Simulation of Aging Effects on Face Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Log-polar Stereo for Anthropomorphic Robots
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Face Verification across Age Progression
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Face Processing: Advanced Modeling and Methods
Face Processing: Advanced Modeling and Methods
Distinctiveness of faces: A computational approach
ACM Transactions on Applied Perception (TAP)
2D and 3D face recognition: A survey
Pattern Recognition Letters
Automatic Age Estimation Based on Facial Aging Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
On finding differences between faces
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Comparing different classifiers for automatic age estimation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A smile can reveal your age: enabling facial dynamics in age estimation
Proceedings of the 20th ACM international conference on Multimedia
Hi-index | 0.00 |
Facial aging has been only partially studied in the past and mostly in a qualitative way. This paper presents a novel approach to the estimation of facial aging aimed to the quantitative evaluation of the changes in facial appearance over time. In particular, the changes both in face shape and texture, due to short-time aging , are considered. The developed framework exploits the concept of "distinctiveness" of facial features and the temporal evolution of such measure. The analysis is performed both at a global and local level to define the features which are more stable over time. Several experiments are performed on publicly available databases with image sequences densely sampled over a time span of several years. The reported results clearly show the potential of the methodology to a number of applications in biometric identification from human faces.