In response to the contemporary demands of digitally recording and instructing Kunqu Opera body movements, this paper proposes a digital intelligence framework that integrates Laban Movement Theory with multi-modal data acquisition technologies. Centered on the basic skills techniques of Kunqu opera body movements, the study develops a digital Labanotation generation method, supported by multi-modal data collection and symbolic mapping, to accurately extract and standardize key features of stylized body patterns. Further, the generated labanotations are integrated into an interactively designed visual learning platform that combines 3D virtual characters with structured symbolic representation, offering learners a multi-modal instructional environment that merges analytical rigor with intuitive perception.Together, these components constitute a unified framework that advances the scientific documentation and teaching of Kunqu Opera movements, while providing a scalable solution for the intelligent preservation and dissemination of intangible cultural heritage in the digital era.
