Fast DCT based expression extraction and lifelike transferring for facial images

Facial expression details are important visual cues to interpret expressions, which are also hard to be synthesized. We propose a novel facial expression transferring method to synthesize realistic colorful facial expressions with source-specific expression details. First, we choose YUV color space to represent the expression images. In Y channel of the color space, the expression image of the source object is transformed into frequency domain through discrete cosine transform. Then, the expression details including micro-expressions of the source object are extracted through analyzing their frequency distribution. Finally, those expression details are stitched smoothly to the target object with Poisson image editing method. The transferred result is combined with U and V channels of the warped target expression to synthesize the colorful realistic expressions of the target object, which reduces the effect of illumination and skin color variations. Experiments on the Multi-PIE database show that our method has higher perceptual quality over the state-of-the-art methods.