MBIA'11 Proceedings of the First international conference on Multimodal brain image analysis
Age estimation using multi-label learning
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Human age estimation using ranking SVM
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
Relative forest for attribute prediction
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
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In this paper, we propose an ordinal hyperplane ranking algorithm called OHRank, which estimates human ages via facial images. The design of the algorithm is based on the relative order information among the age labels in a database. Each ordinal hyperplane separates all the facial images into two groups according to the relative order, and a cost-sensitive property is exploited to find better hyperplanes based on the classification costs. Human ages are inferred by aggregating a set of preferences from the ordinal hyperplanes with their cost sensitivities. Our experimental results demonstrate that the proposed approach outperforms conventional multiclass-based and regression-based approaches as well as recently developed ranking-based age estimation approaches.