LAUSR

In the last decade, demographic profiling from facial imagery has grown in its importance in the computer vision field. For demographic profiling, we usually mean gender, ethnicity, and age identification from face images. In this paper, we propose an efficient and effective profiling framework and we assess the quality of the proposed approach comparing the results obtained by our system with those achieved by other recently published methods on large datasets of facial images with different age, gender, and ethnicity. These results show how a carefully engineered pipeline of efficient image analysis and pattern recognition techniques leads to state-of-the-art results at 20 FPS using a single thread on a 1.6 GHZ i5-2467M processor.