Personalized Smart Clothing Design Based on Multimodal Visual Data Detection

Abstract

In the traditional clothing customization system, only the designer participates in the clothing design, and the style is single. In the face of numerous styles, the user just repeatedly arranges and combines the styles, but does not realize the user’s innovative design. In this paper, we propose a novel multitask deep convolutional neural network training method for task-by-task transfer learning, and learn deep image features for image retrieval tasks on noisy user click data. Image retrieval model based on image-text multimodal correlation features: this paper uses image-text multimodal correlation features to calculate the correlation between query keywords and images, and calculates the correlation between images and images. In this paper, the method of automatic generation of clothing style is researched, and parameterized coding is designed for it. Taking the typical style of suits as the initial population, through the human-computer interaction interface, the scoring value is assigned to the fitness value to carry out the evolution process. The binary string of the suit style generated by the genetic algorithm is decoded through the decoding algorithm and rules, decoded into a visual style diagram of the style of the suit style, and the style diagram of the suit style is automatically drawn. From the perspective of clothing design, this paper summarizes the general design methods of outdoor sports smart clothing, follows the integration of people-clothing-environment, and proposes a wearer-centered design concept to deeply explore the rationality of outdoor sports smart clothing design methods. This paper further solves the key problems in the design process, and takes the fashion of clothing as the core principle to design the structure of clothing modeling. The fabric selection of suits is based on the principle of clothing comfort. The key is to realize the outdoor sports monitoring function of suits through sensing technology. The design uses Arduino as an electronic prototype platform, so as to detect the heart rate of the human body during exercise and the microclimate temperature under the clothes. This kind of suit with monitoring function is ultimately a combination of sensing device and clothing. It not only has monitoring function, but also has the aesthetic concept of clothing design and conforms to the performance of human body structure, which will provide reference and reference for the design of outdoor sports smart clothing.

Clothing Design Style Recommendation Using Optimized Semantic-Preserved Generative Adversarial Network

“…Deng and Liu [22] have suggested PSCD-DNN-MVDD. When faced with a variety of styles in this paper, the user simply continually arranges and combines the styles without realizing their own unique look.…”

Application of Clothing Design Based on Computer Vision Technology Using Hybrid Graph Convolution Neural Network and Lotus Effect Optimization Algorithm

“…Many costume designers may find inspiration in the vibrant sculptures and rich, enchanting depictions of medieval garments preserved in the murals at the Mogao Caves in Dunhuang, which date back thousands of years [5]. These days, computer vision research is mostly focused on the automatic identification of national attire using image recognition technologies [6]. Next, local fine-grained features and a bag-of-words model, like the scale-invariant feature's transform, were used to identify garments belonging to the She nationality that had comparable shapes [7].…”