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A proposal of a solution for age band prediction from human faces

The purpose of this work is to propose a predictive model of a subject's age band. It is made under marketing constraints; these constraints define the customer's behavior towards five age bands. In this context, we first propose a regression approach, with Partial Least Squares Regression and Support Vector Regression. We then propose a classification approach by combining Support Vector Machines and Classification and Regression Tree. The classification approach overcomes the regression approach. In both approaches, we use Multi-Scale and Multilevel Histogram of Blocks of Local Binary Patterns (MMHLBP) as texture descriptor. Eventually, a comparison between our final model and the human operator shows the relevancy of the classification approach.