# Human Age Estimation Method Robust to Camera Sensor and/or Face Movement

## TL;DR

This paper introduces a method to improve age estimation from face images by making systems more robust to motion blurring caused by camera or face movement.

## Contribution

The novel contribution is a method to enhance age estimation performance by addressing motion blurring effects.

## Key findings

- Motion blurring significantly degrades age estimation performance.
- The proposed method improves system robustness and efficiency in age estimation.
- Experiments show better performance compared to systems without the proposed method.

## Abstract

Human age can be employed in many useful real-life applications, such as customer service systems, automatic vending machines, entertainment, etc. In order to obtain age information, image-based age estimation systems have been developed using information from the human face. However, limitations exist for current age estimation systems because of the various factors of camera motion and optical blurring, facial expressions, gender, etc. Motion blurring can usually be presented on face images by the movement of the camera sensor and/or the movement of the face during image acquisition. Therefore, the facial feature in captured images can be transformed according to the amount of motion, which causes performance degradation of age estimation systems. In this paper, the problem caused by motion blurring is addressed and its solution is proposed in order to make age estimation systems robust to the effects of motion blurring. Experiment results show that our method is more efficient for enhancing age estimation performance compared with systems that do not employ our method.