A Hybrid Workflow for Animation-Ready Digital Humans with Morph Target Optimization

High-fidelity digital humans are increasingly demanded in film, virtual broadcasting, and immersive applications. However, traditional manual modeling is labor-intensive, while purely generative approaches often lack anatomical precision. We present a hybrid workflow that integrates manual modeling with AI-assisted generation, combining high-precision cervicocranial scanning, Character Creator 4 "Mesh to Head"processing, and MetaHuman-based morph target design for enhanced lip-sync realism. Compared to conventional pipelines, our method reduces manual workload and iteration time while ensuring animation readiness. Quantitative evaluation using the Structural Similarity Index Measure (SSIM = 0.6485) and qualitative expert assessments confirm both structural fidelity and perceptual realism. This workflow effectively bridges raw scan data and production-ready assets, enabling scalable creation of photorealistic digital humans.