Child face detection using age specific luminance invariant geometric descriptor

While considerable research have been conducted on age-wise age estimation using skin detection most often with other visual cues, relatively little research has looked closely at the subject. In this paper, we present a new framework for interpreting facial image patterns that can be employed in categorical age estimation. The aim is to propose a novel approach to investigate and implement a child face detection technique that is able to estimate age categorically adult or child based on a new hybrid feature descriptor. The novel hybrid feature descriptor LIGD (the luminance invariant geometric descriptor) is composed of some low and high level features, which are found to be effective in characterizing the local appearance. In local appearance estimation, chromaticity, texture, and positional information of few facial visual cues can be employed simultaneously. Compared to the results published in a recent work, our proposed approach yields the highest precision and recall, and overall accuracy in recognition.