Body-based human age estimation at a distance

Estimating human ages at a distance has many potential applications, especially for visual surveillance in such places as supermarkets and airports. In this paper, we propose a new human age estimation approach from full body images with frontal or back views. Given a body image, we extract local SIFT features from body image patches and learn sparse coefficients for body image feature representation, followed by a regressor for age prediction. Experimental results have clearly demonstrated the feasibility of using fully body images to estimate human age and the effectiveness of our proposed approach.