A New Method for Age Estimation from Facial Images by Hierarchical Model
Proceedings of the Second International Conference on Innovative Computing and Cloud Computing
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In our daily life, it is much easier to distinguish which person is elder between two persons than how old a person is. When inferring a person's age, we may compare his or her face with many people whose ages are known, resulting in a series of comparative results, and then we conjecture the age based on the comparisons. This process involves numerous pairwise preferences information obtained by a series of queries, where each query compares the target person's face to those faces in a database. In this paper, we propose a ranking-based framework consisting of a set of binary queries. Each query collects a binary-classification-based comparison result. All the query results are then fused to predict the age. Experimental results show that our approach performs better than traditional multi-class-based and regression-based approaches for age estimation.