Synthesis of Facial Images Based on Relevance Feedback

We propose a dialogic system based on a relevance feedback strategy that allows for the semiautomatic synthesis of a facial image that only exists in a user's mind. The user is presented with several facial images and judges whether each one resembles the face that he or she is imagining. Based on the feedback from the user, a set of sample facial images are used to train an Optimum-Path Forest classifying the relevance of facial images. An interpolation method is then employed to synthesize new facial images that closely resemble the imagined face. A series of experiments are conducted to evaluate and verify the effectiveness and efficiency of the proposed technique.