Photo rating of facial pictures based on image segmentation

A single glance at a face is enough to infer a first impression about someone. With the increasing amount of pictures available, selecting the most suitable picture for a given use is a difficult task. This work focuses on the estimation of the image quality of facial portraits. Some image quality features are extracted such as blur, color representation, illumination and it is shown that concerning facial picture rating, it is better to estimate each feature on the different picture parts (background and foreground). The performance of the proposed image quality estimator is evaluated and compared with a subjective facial picture quality estimation experiment.

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