Age estimation at a distance has potential applications including visual surveillance and monitoring in public places. Far from the camera, image resolution is significantly degraded. In fact, age estimation using classical methods such as face is not reliable. Given that gait is very sensitive to ageing, gait analysis is the suitable solution for age estimation at a great distance from the camera. Medical and biomechanical studies prove that older adults adapt their walking toward a safer and more stable gait and an established balance. Indeed, in this study the authors propose a gait-based descriptor for age classification using a silhouette projection model. The proposed model encapsulates both spatiotemporal longitudinal (SLP) and transverse (STP) projections of the silhouette during a gait cycle. The proposed model aims to represent the arms' swing, the head's pitch, the hunched posture and the stride's length, which are among the most outstanding ageing characteristics that appear on the elderly's gait. Although age classification using gait is a very challenging task, SLP and STP curves analysis shows a considerable discrimination between young and elderly people. Also, experiments conducted on the OU-ISIR database prove that their proposed descriptor outperforms existing ones by reaching an important recognition rate.

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Far from the camera, image resolution is significantly degraded and person cannot cooperate with the acquisition equipment. So, the classical intrusive biometrics approach could not be applied. As a non-intrusive biometric, gait analysis gained the attention of the computer vision community for number of potential applications such as age estimation. Since, that gait is very sensitive to ageing, gait analysis is the suitable solution for age estimation at a great distance from the camera. Given the complexity of this task, the authors propose in this study a new approach based on descriptors cascade. The proposed approach is to use a fusion of some efficient contour and silhouette descriptors. Indeed, they introduce the proposed descriptor based on silhouette projection model (SM) in the first time. In the second time, the proposed descriptor is merged with the best existing ones in order to enhance the classification performances. Despite that age classification using gait is a very challenging task, experiments conducted on OU-ISIR database show that their proposed descriptors fusion approach enhances considerably the recognition rate.

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