Age estimation based on extended non-negative matrix factorization

Ce Zhan, Wanqing Li, Philip Ogunbona
2011 2011 IEEE 13th International Workshop on Multimedia Signal Processing  
Previous studies suggested that local appearance-based methods are more efficient than geometric-based and holistic methods for age estimation. This is mainly due to the fact that age information are usually encoded by the local features such as wrinkles and skin texture on the forehead or at the eye corners. However, the variations of theses features caused by other factors such as identity, expression, pose and lighting may be larger than that caused by aging. Thus, one of the key challenges
more » ... f age estimation lies in constructing a feature space that could successfully recovers age information while ignoring other sources of variations. In this paper, non-negative matrix factorization (NMF) is extended to learn a localized non-overlapping subspace representation for age estimation. To emphasize the appearance variation in aging, one individual extended NMF subspace is learned for each age or age group. The age or age group of a given face image is then estimated based on its reconstruction error after being projected into the learned age subspaces. Furthermore, a coarse to fine scheme is employed for exact age estimation, so that the age is estimated within the preclassified age groups. Cross-database tests are conducted using FG-NET and MORPH databases to evaluate the proposed method. Experimental results have demonstrated the efficacy of the method.
doi:10.1109/mmsp.2011.6093779 dblp:conf/mmsp/ZhanLO11 fatcat:dj25dhwfnzb77m7q2j674mh37e