The improvement of the realism of digital character emotional expression has become an important breakthrough in the field of 3D modeling, and the intervention of artificial intelligence technology has brought a paradigm innovation to the expression mapping mechanism. Traditional facial binding technology relies on manual adjustment of the weight of blended shapes, which is difficult to capture the dynamic gradient features of emotional states, while the expression generation algorithm based on deep learning can establish the quantitative association between emotional semantics and muscle movement. This technological transformation not only changes the production process of character animation, but also promotes the evolution of virtual characters from visual realism to emotional intelligence. In application scenarios such as virtual idols and intelligent customer service, the mapping accuracy of emotion algorithms directly affects the user's immersive experience and interactive trust, which makes the optimization of expression mapping path a hot spot in interdisciplinary research.

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