Parametric Reshaping of Portrait Images for Weight-change Simulation


IEEE Computer Graphics and Applications, 2018, 38(1): 77-90.

Haiming Zhao, Xiaogang Jin, Xiaojian Huang, Menglei Chai, and Kun Zhou



Our parametric facial reshaping method automatically simulates the weight-change of a 2D portrait image and generates a fatter or thinner face as intended. (Middle) is the original input image of Albert Einstein; (left) is the result of reshaping degree -2, which indicates losing weight by 2 degrees; (right) is the result of reshaping degree +2, which implies gaining weight by 2 degrees.

Comparison results. (b-d) and (g-i) are camera images. (a), (e), (f), (j) are our reshaping results.


We present an easy-to-use parametric image retouching method for thinning or fattening a face in a single portrait image while maintaining a close similarity to the source image. First, our method reconstructs a 3D face from the input face image using a morphable model. Second, according to the linear regression equation derived from the depth statistics of the soft tissue in the face and the user-set parameters of reshaping degree, we calculate the new positions of the feature points. Third, the Laplacian deformation method is employed to calculate the deformed positions of non-feature points in the 3D face model. Finally, we seamlessly blend the projected reshaped face region in 2D image with the background using image retargeting method based on mesh parametrization. Our model-based reshaping process can achieve globally consistent editing effects without noticeable artifacts. The effectiveness of our algorithm is demonstrated by experiments and user study.