Research and Application of 3D Clothing Design Based on Deep Learning

In order to fully explore the multi-scale features of 3D clothing design, at the same time, so as to realize the extraction of the clothing itself and the overall characteristics of the clothing, a research and application of 3D clothing design based on deep learning is proposed. Deep learning neural network model is applied to recognize 3D human shape features, the characteristic line is obtained by the threshold judgment, feature points are obtained based on the identified feature lines, the body circumference curve is fitted, and the measurement of human body size is realized. Simulation results show that for the training of convolutional neural networks in the research of feature recognition algorithms the final feature recognition accuracy is made to reach 92.56%. The training network based on the front projection has a good recognition effect for the neck, armpit, and waist, while the side projection has a good recognition effect for the back neck, shoulder, chest, waist, and buttocks. In general, the characteristic lines of the key parts of the human body have been effectively identified. The author uses convolutional neural networks in deep learning, carrying out 3D scanning human body feature recognition, a large number of experiments have verified the effectiveness and feasibility of the algorithm.