Product color emotional design based on a convolutional neural network and search neural network

Due to the growing trend of social manufacturing, product design has focused on meeting the emotional needs of users. As a product attribute, color plays an important role in meeting these needs. Therefore, product color emotional design has attracted the attention of researchers. However, a user's perception of the emotional image of product color is highly complex, and it is difficult to define this perception accurately. To this end, based on the theoretical framework of Kansei engineering, this study proposes a product color emotional design method based on a convolutional neural network and a search neural network. First, we implement a semantic differential experiment to ascertain the user's color image. Then we use a convolutional neural network to establish a complex association model between the product color and the user's emotional imagery. Based on this model, the search neural network is used to search and generate the product color design scheme that meets the target image. Finally, a product color design system applicable to practical design problems is developed. An example of the design of a home service robot demonstrates that the proposed method and system provides accurate product color design solutions that meet the needs of the user's emotional image and can be used to develop practical large-scale applications of product color emotional design theory and methods.

Automated summary

With the increasing trend of social manufacturing, product design has shifted towards meeting the emotional needs of users, with color playing a significant role in this aspect. Researchers have focused on product color emotional design, but it is challenging to accurately define a user's perception of the emotional image of product color, which is highly complex.