Seldom does a photograph record what we perceive with our eyes. As a result

we could not obtain an optimal photo with all the subjects smiling as expected. When taking pictures

we spend a considerable amount of time capturing other shots and inadvertently miss beautiful scenes. Traditional photo editing apps could not facilitate expression editing. Hence

we develop an algorithm for interactive photo editing based on expression transmission to edit parts of faces with poor expression. The proposed algorithm uses scan line deformation or feature point deformation on the basis of the identity related to the source face. Our approach is to utilize target face expression to edit source faces with unsatisfied expressions. The result shares an expression similar to that of the target face. The face is edited by relighting and then finally fused in the photo. The proposed algorithm can edit frontal face images to achieve desired expressions. This algorithm

which is based on different processing conditions and transmission models

demonstrate better performance than the conventional Gaussian mixture model with regard to the test results. This study proposes a novel expression transmission model. We assign different transmission models for different pieces of target face identity information and subsequently introduce interaction. Experiment results indicate that our model achieves preferable adaptive performance when applied in photos with different conditions and requirements.