Affiliations: [a] Department of Education, Jizhong Vocational College, China | [b] Department of Information Engineering, Jizhong Vocational College, China | [c] Students’ Affairs Office, Jizhong Vocational College, China
Abstract: With the development of technology and the improvement of living standards, consumer demand for toy products has also changed. More people are showing strong interest and demand for digital toy products. However, in the current digital toy design process, extracting the hairstyle features of the doll’s head is still a challenge. Therefore, this study extracts the two-dimensional contour of the target hairstyle and matches it with the template hairstyle in the database. Then, combining hair texture information and hairstyle structural features, fine geometric texture details are generated on the hairstyle mesh surface. Finally, a doll head modeling method based on model matching and texture generation is proposed. The results showed that the hairstyle of the Generative model was almost the same as the real hairstyle. Compared with the modeling methods based on interactive genetic algorithm and digital image, the average F1 value of this method was 0.95, and the mean absolute error was the smallest. The accuracy of the target model modeling was 95.4%, and the area enclosed by the receiver operating characteristic curve and coordinate axis was 0.965. In summary, the doll head modeling method based on model matching and texture generation proposed in this study can generate high-precision and realistic hairstyle models corresponding to the hairstyle. The overall shape and local geometric details of the hairstyle can meet the needs of 3D printing, providing certain reference significance for hairstyle reconstruction.
Keywords: Model matching, geometric texture, hairstyle reconstruction, 3D printing, head modeling
