As a mode of perpetuating and revitalizing traditional culture, cultural and creative products have garnered widespread affection and recognition from the public. In the context of evolving societal trends and advancements in science and technology, the digitization of traditional cultural and creative products has emerged as a prominent trend. This study undertakes the digital design of these products, primarily focusing on the innovative application of a style transfer algorithm to traditional motifs, supplemented by their visualization through digital platforms such as augmented reality (AR) and virtual reality (VR). Furthermore, it facilitates intelligent consumer interaction via gesture recognition algorithms, thereby enhancing user engagement and experience. During the implementation phase, this research conducts comparative analyses of style transfer and gesture recognition within digital cultural and creative products. It also employs the Kano questionnaire to categorize and analyze user needs effectively. Notably, while the recall rate of the style transfer algorithm documented in this study remains below 0.9, it consistently achieves high precision, significantly enhances feature extraction capabilities, and improves the quality of the style transfer effects produced. Moreover, the static gesture recognition algorithm achieves an impressive average recognition rate of 98.2%. The dynamic gesture recognition algorithm, meanwhile, maintains an average recognition rate of 94% with a processing time of 3.2 seconds, balancing the demands of real-time interaction and accuracy effectively. This study systematically analyzes the significance of each requirement element across six dimensions, classifying customer needs for digital cultural and creative products into four distinct categories. Additionally, it delineates a viable pathway for the integration of digital art elements into the design of artistic and innovative products, setting a foundation for future innovations in this field.