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1.1 Background of the Study
Clothing can be looked at from a variety of perspectives. It can be described in physical terms with respect to thermal resistance or insulation (Gagge, 1941 and Ashrae, 1997) and its impedance to mass (water vapor) transfer (Woodcock, 1962, Goldman, 1981). From an ergonomist’s perspective, clothing can be regarded as a mechanism capable of making a workplace environment safer and healthier for workers, or in some cases, present a workplace hazard. From an anthropological perspective, clothing represents a significant cultural development that has, along with shelter and fire, allowed the species to venture well outside its original tropical domain (McIntyre, 1980; Clark & Edholm, 1985 and Parsons, 1993). From a social angle, clothing can be variously thought of as a projection of personality, mood, religion, sub-cult and other group affiliations. Clothing also represents a code for organizational or corporate identity, and of course, it is very commonly used to convey socio-economic status cues. But in conventional thermal comfort theory, perhaps most eloquently described by Fanger in 1970, clothing simply represents a single layer of thermal insulation uniformly interposed between the human subject’s body surface and their immediate thermal environment.
Driven by the huge potential profit in clothing market, clothing classification (Yannis Kalantidis, 2013; Lukas Bossard, 2012 and Junshi Huang, 2015), attributes recognition (Hadi Kiapour, 2014; Evan Shelhamer, 2014 and Edgar Simoserra, 2015), and clothing retrieval (Hadi Kiapour, 2015; Xiaodan Liang, 2016 and Zongmin Li, 2016) is receiving increasing interest in recent years. Clothing recommendation is new-branch research work. When people choose to clothe to wear, weather information is the most important factor. As shown in Figure 1, different weather categories generally pose their own distinctive dresses. Assume that when you get up in the morning, the system will suggest the most suitable clothing for you. What a fantastic day it is!
However, how to define the weather category is a key problem. In this project, we explore how to explain the weather category and study a new topic of weather-oriented clothing recommendation.
Fig. 1. The weather-oriented clothing recommendation system can automatically suggest the most suitable clothing from the user’s album based on the different weather information obtained from the user inputting.
Firstly, the system can obtain weather information from the user inputting or automatically acquire from websites, including temperature, humidity, wind scale, sunshine, rain, snow, overcast. Then these weather information will be classified into 12 categories according to China Meteorological Administration (http://www.cma.gov.cn/) suggested weather-clothing-classification.
Weather-to-Garment system aims at two clothing recommendation scenarios. As shown in Figure 2. Firstly, a user can specify weather information, the system can recommend the most suitable clothing items from users’ own album.
Secondly, when the user inputs one reference clothing item, the Weather-to-Garment system can suggest the most pairing clothing items, which are also suitable to the weather category.
As far as we know, this is the first work to solve this practical problem in the computer vision field.
Through experiments, we observe that it is infeasible match weather category using low-level features extracted from clothing images directly. The reason is that there exists a big gap between low-level features and high-level weather categories. To narrow the semantic gap, we adopt middle level clothing attributes as a bridge. In our work, we show that clothing recommendations can benefit from attributes learning that simultaneously optimizes a scoring function taken into visual features and clothing attributes classification. Here we define 10 multi-value clothing attributes, including the category attribute and some detail attributes, which is used to describe certain properties of clothing.
To learn the weather-oriented clothing recommendation model, we define a scoring function. The function includes three potential terms to model the relationships. We use the multi-class Support Vector Machine (SVM) to learn clothing attributes recognition.
Fig. 2. The weather-oriented clothing recommendation system includes two scenarios. Firstly, a user can specify weather information, the system can recommend the most suitable clothing items from users’ own album. Secondly, when the user inputs one reference clothing item, the Weather-to-Garment system can suggest the most pairing clothing items, which are also suitable for the weather category.
The fashion industry occupies a significant position in the global economy and involves large industrial chain, including garment design, production, and sales. In fact, in recent years, there has been an expanding demand for clothing all over the world. Since 2008, garment sales have increased by $3.3 billion every year, and the global garment sales reached $1.25 trillion in 2012 (OECD, 2014). According to a report of Euro monitor International, in 2015, the growth rate of clothing sales was 4.5%, and the industry gross reached $1.6 trillion. The global clothing sales enhanced by 3.8% and the industry gross rose to $1.7 trillion in 2016. The above data show that the garment industry is developing at a rapid rate.
In fashion sales, the recommendation technology, as an emerging technology, has attracted wide attention from scholars.
As is widely known, the traditional garment recommendation depends on manual operation. To be specific, salesmen need to recommend garment to customers in order to arouse their interest in purchasing. However, it is very difficult for salesmen to understand customers’ real thoughts and then recommend the targeted garment as there is no sufficient cohesiveness between customer information and merchants.
Therefore, it is essential and meaningful to find a set of objective indicators, instead of subjective opinions, to evaluate the fashion level in the clothing recommendation technology.
As Internet technology continues to develop rapidly, virtual fitting and other clothing intelligent equipment have enjoyed great popularity in the fashion industry. Cordier, 2003 first applied the 3D graphics technology to create and simulate the virtual store. Subsequently, Li and Zou, 2011 proposed the interactive 3D virtual fitting room system, in which the model’s hairstyle and accessories can be changed according to customers’ preferences and customers’ matching degrees can be evaluated to guide people to choose the suitable clothes. Nevertheless, virtual fitting research products are constantly innovating and developing. In fact, today’s systems are mainly used to display garments, and customers can only have a preview of the fitting effect. If the store does not have an efficient recommended method, the search will be tedious and frustrating. Zhang, 2008 presented an interaction clothes fitting system that can recognize what human eyes perceive in terms of the clothing similarity through the frontal-view outfit images. Limaksornkul, 2014 put forward the Closet Application to record the clothing statistics and accessories that are frequently used to recommend clothes to customers according to the statistics of their purchasing history. The recommended technology not only allows customers to quickly find the right clothes in the fitting process but also helps businesses increase sales. Nonetheless, the above methods are mainly based on the subjective views that ignore objective data. To address this problem, this project proposes a fashion level evaluation method for clothing recommendations based on the weather and weak appearance feature.
1.2 Statement of Problem
The general problem addressed in this report is the one presenting applications to the user of a web or mobile device in a way that minimizes the information overload, i.e. the difficulty a person has to make a decision caused by the presence of too much information. The effort in terms of time and cognitive work a user puts into finding interesting and relevant cloth to wear base on a weather scenario should be as low as possible. This problem was divided into sub-problems, namely; collecting and storing application metadata; collecting and storing user consumption of applications; filtering out less interesting applications, and presenting the interesting ones to the user. Both men and women struggle with the process of choosing outfits on a daily basis, this is based on different reasons example is the weather, making a clothing recommender system a support tool for their daily life is the best method to solve this problem. Everybody has their good and bad days and we want to create an RS that is able to provide suggestions based on the environment weather. It will not only consider the occasion, style, weather and temperature of the day but also his/her emotional status providing personalized suggestions.
1.3 Aim and Objective of the Study
The main aim and objective of this study are to design and implement weather-based clothing recommender system. The specific objective of this study is:
1. to examine the usefulness and analyze the recommendation system in general
2. to develop a web applications that can help to determine the type of cloth to wear base on the weather.
1.4 Significance of the Study
The projects provide a flexible framework for exploring curricular topics and engaging students in developing important 21st-century skills such as communication, teamwork and technology skills. In addition, students are inspired by the fun and creative format and the opportunity to make new friends around the world. This proposed research work will add to the existing body of knowledge and provide new software for weather-based clothing recommender systems.
1.5 Scope of the Study
The scope of this study is center on design, development, and implementation of web-based applications for weather clothing recommendation system and the research will be restricted to the web application.
1.6 Limitation of the Study
Generally, each work has some limitations and this study is not exempted.
The three major limitations of this study are high programming technology as well as financial constraints and lack of time. The constraint of high programming techniques in PHP, JQUERY and MYSQL prevent the researcher from doing in-depth study and analysis of the subject. While the issue of financial constraint limits the frequency of investigation towards/from the institution towards collecting the necessary information related to the study. And lack of time- researchers will engage in this study together with other academic tasks. This will result in a reduction in time devoted to research work.
1.7 Definition of Terms
Recommendation System: A recommender system, or a recommendation system (sometimes replacing ‘system’ with a synonym such as a platform or engine), is a subclass of information filtering system that seeks to predict the “rating” or “preference” a user would give to an item. They are primarily used in commercial applications.
Weather forecasting: is the application of science and technology to predict the conditions of the atmosphere for a given location and time.
HTML CODE: – HTML stands for HyperText Markup Language. It is a type of computer language that is primarily used for files that are posted on the internet and viewed by web browsers. HTML files can also be sent via email.
Markup language: – A markup language is a combination of words and symbols which give instructions on how a document should appear. For example, a tag may indicate that words are written in italics or bold type.
Web browser: -A Web browser is a software program that interprets the coding language of the World Wide Web in graphic form, displaying the translation rather than the coding. This allows anyone to “browse the Web” by simple point and click navigation, bypassing the need to know commands used in software languages.
File extension: – A file extension is a suffix at the end of a filename that tells a computer, and the computer user, which program is needed to open the file. Also called a filename extension, this suffix preceded by at least one period, is generally one to five characters long but the norm is usually three characters in length.
Email: – Email, also sometimes written as e-mail, is simply the shortened form of electronic mail, a protocol for receiving, sending, and storing electronic messages. An email has gained popularity with the spread of the Internet. In many cases, email has become the preferred method of communication.
TCP/IP: – This often used but little understood set of operations stands for Transmission Control Protocol/Internet Protocol. TCP/IP is the combination of the two and describes the set of protocols that allows hosts to connect to the Internet. In actuality, TCP/IP is a combination of “more than those two protocols, but the TCP and IP parts of TCP/IP are the main ones and the only ones to become part of the acronym that describes the operations involved.
TEXT FILE: – A text file is a computer file that stores a typed document as a series of alphanumeric characters, usually without visual formatting information. The content may be a personal note or list, a journal or newspaper article, a book, or any other text that can be rendered accurately in typewritten form.
HyperLink: -A hyperlink is a graphic or a piece of text in an Internet document that can connect readers to another webpage, or another portion of a document. Web-users will usually find at least one hyperlink on every webpage. The simplest form of these is called an embedded text or an embedded link.
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