3D image processing technology based on interactive entertainment application in cultural and creative product design

Abstract

3D printing technology has many advantages that traditional production models do not have, greatly accelerating the speed of product design and development. In order to achieve the application of machine learning based 3D image processing technology in cultural and creative product design, this article collects a large amount of 3D image data as training samples and uses machine learning algorithms to establish a training model. Considering the characteristics of the data and the processing objectives, these 3D image data are used as a training set and trained through machine learning algorithms to learn the features and patterns of the image. After the training is completed, use this model to process the new 3D image. By inputting new image data, the model automatically extracts image features and predicts and processes them based on previously learned patterns. Evaluate the advantages and disadvantages of machine learning based methods in processing complex 3D images by comparing experimental results. The experimental results show that machine learning based 3D image processing technology has high accuracy and efficiency in the design of cultural and creative products. Compared with traditional methods, this method can better process complex 3D images and provide better design effects.