ИСТИНА

This report presents a method for generating three-dimensional facial expressions from a given neutral geometry, based on a local shape model and a small set of training data. The facial geometry is pre-segmented into anatomically meaningful regions, and deformation parameters are estimated for each region with respect to data fidelity and boundary consistency. After approximating the neutral shape, expressions are synthesized and transferred back to the original geometry while preserving anatomical structure. The proposed approach ensures a high degree of expressiveness and consistency across expressions while maintaining subject-specific facial features. Experimental results demonstrate its superiority over ex-isting methods under limited data conditions.