KR-20260065150-A - User-Customized Clothing Recommendation and Coordination System Based on Situation Prediction

Abstract

The present invention relates to a clothing recommendation and styling suggestion system optimized for the user's situation and needs. The system of the present invention is characterized by analyzing multiple clothing images owned by the user and predicting and recommending clothing that the user may need in the future based on the user's schedule, location information, and past preferences. First, it receives clothing images owned by the user, analyzes the material, timing of wear, and purpose of wear, and identifies detailed characteristics of the clothing through a deep learning-based image classification model. Subsequently, it analyzes the user's schedule and location information to predict upcoming events and recommends optimal clothing suitable for them. The recommended clothing is suggested to enable styling that harmonizes with clothing already owned by the user, thereby allowing the user to try various styling options without purchasing new clothing. The system of the present invention provides the effect of maximizing the utilization of clothing owned by the user and reducing unnecessary consumption.

Inventors

• 조태식

Assignees

• 조태식

Dates

Publication Date

20260508

Application Date

20241101

Claims (5)

1. A clothing recommendation method executed by a computer device, comprising: receiving a plurality of clothing images from a user terminal; analyzing each of the received clothing images to determine the material, time of wearing, and purpose of wearing; analyzing at least one of the user's calendar information, photo information, and location information to predict an expected event; and recommending clothing suitable for the predicted event based on the determined material, time of wearing, and purpose of wearing information.
2. A clothing recommendation method according to claim 1, wherein the clothing image analysis step comprises the step of analyzing pixel values of the clothing image using a deep learning-based image classification model.
3. A clothing recommendation method according to claim 1, wherein the expected event includes at least one of a wedding, a dinner party, and a date.
4. A clothing recommendation method according to claim 1, further comprising the step of delivering the recommended clothing to a user or suggesting a coordinated outfit by combining it with the user's existing clothing.
5. A computer program characterized by including program code for executing a clothing recommendation method described in any one of claims 1 to 4 on a computer.

Description

User-Customized Clothing Recommendation and Coordination System Based on Situation Prediction The present invention relates to a user-customized, situation-predicting-based clothing recommendation and styling suggestion system. With the recent rapid changes in clothing consumption and fashion trends, there is a growing demand for personalized clothing recommendation services tailored to individual user tastes and needs. While existing online shopping malls and fashion platforms include features to recommend various products, they often limit themselves to simply recommending items based primarily on users' click history or purchasing patterns. This approach not only fails to adequately reflect users' actual needs but also lacks clothing recommendations optimized for specific situations, which can lead to low user satisfaction. Furthermore, users often struggle to optimize and manage their wardrobes and fail to make the most of the clothes they possess. Consequently, users continue to purchase new clothing despite having enough, which can lead to overconsumption. A system that recommends outfits by considering the harmonious matching of each item during the selection and styling process would allow users to utilize their existing clothing more effectively. Accordingly, a recommendation system based on currently owned clothing is required. Due to recent technological advancements, image analysis technology utilizing AI and deep learning has advanced significantly. This has made it possible to precisely analyze images of clothing owned by a user to identify materials, styles, and seasonality. Furthermore, methods that predict and recommend clothing the user may need in the future by comprehensively analyzing various data such as the user's schedule, location, and preferences are gaining attention. FIG. 1 is a drawing illustrating an example of an operating environment of a system according to one embodiment of the present specification. FIG. 2 is a block diagram for explaining the internal configuration of a computing device in one embodiment of the present specification. FIG. 3 is a block diagram illustrating a service processing unit and its configuration according to an embodiment of the present invention. FIG. 4 is a block diagram illustrating a laundry processing prediction information calculation unit and its detailed configuration according to an embodiment of the present invention. FIG. 5 is a flowchart illustrating the operation of a computing device according to an embodiment of the present invention. FIGS. 6 to 9 are drawings illustrating an interface output from a user device according to an embodiment of the present invention. In describing the embodiments of this specification, if it is determined that a detailed description of known configurations or functions could obscure the essence of the embodiments of this specification, such detailed description is omitted. Additionally, parts of the drawings unrelated to the description of the embodiments of this specification have been omitted, and similar parts are denoted by similar reference numerals. In the embodiments of this specification, when a component is described as being "connected," "combined," or "joined" with another component, this may include not only a direct connection but also an indirect connection in which another component exists in between. Furthermore, when a component is described as "comprising" or "having" another component, this means that, unless specifically stated otherwise, it does not exclude the other component but may include additional components. In the embodiments of this specification, terms such as first, second, etc. are used solely for the purpose of distinguishing one component from another component and do not limit the order or importance of the components unless specifically stated otherwise. Accordingly, within the scope of the embodiments of this specification, the first component in an embodiment may be referred to as the second component in another embodiment, and likewise, the second component in an embodiment may be referred to as the first component in another embodiment. In the embodiments of this specification, distinct components are intended to clearly explain their respective features and do not imply that the components are necessarily separated. That is, multiple components may be integrated to form a single hardware or software unit, or a single component may be distributed to form multiple hardware or software units. Therefore, such integrated or distributed embodiments are included within the scope of the embodiments of this specification, even if not otherwise mentioned. In this specification, the term "network" may encompass both wired and wireless networks. In this context, the network may refer to a communication network where data exchange between devices, systems, and devices can be performed, and is not limited to a specific network. The embodiments described herein may have aspects