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Personalized Smart Clothing Design Based on Multimodal Visual Data Detection

机译:基于多模态视觉数据检测的个性化智能服装设计

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摘要

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.
机译:在传统的服装定制系统中,只有设计师参与服装设计,款式单一。面对琳琅满目的款式,用户只是反复排列和组合款式,却没有实现用户的创新设计。在本文中,我们提出了一种新颖的多任务深度卷积神经网络训练方法,用于逐任务迁移学习,并在有噪声的用户点击数据上学习深度图像特征以进行图像检索任务。基于图文多模态关联特征的图像检索模型:利用图文多模态关联特征计算查询关键词与图像的相关性,计算图像与图像的相关性。该文研究了服装款式的自动生成方法,并针对该方法设计了参数化编码方法。以典型款式的西装为初始人群,通过人机交互界面,将评分值分配给适应度值,进行演化过程。遗传算法生成的西服样式的二进制字符串通过解码算法和规则进行解码,解码成西服样式的视觉样式图,自动绘制出西服样式的样式图。本文从服装设计的角度,总结了户外运动智能服装的一般设计方法,遵循人-衣-环境的融合,提出了以穿着者为中心的设计理念,深入探讨了户外运动智能服装设计方法的合理性。本文进一步解决了设计过程中的关键问题,以服装的时尚为核心原则,设计了服装造型的结构。西装的面料选择是以服装舒适性为原则的。关键是通过传感技术实现西装的户外运动监控功能。该设计使用Arduino作为电子原型平台,从而检测人体在运动时的心率和衣服下的小气候温度。这种具有监控功能的防护服,归根结底是传感装置和服装的结合。它不仅具有监控功能,而且具有服装设计的美学理念,符合人体结构的表现,将为户外运动智能服装的设计提供参考和借鉴。

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