Sistema de recomendación de prendas basado en reconocimiento corporal (SISCORP)

During the last few years, technology has evolved rapidly, and many startups have emerged and consolidated. In particular, the last two years have been a challenge for companies and businesses worldwide due to the pandemic that has affected most sectors, further driving the need for digital adaptation and transformation. Under this context, businesses whose main sales channel was in-person were forced to digitize as soon as possible, if they had not already done so, to survive in this highly competitive business world. Nowadays, it is essential for a startup or business to be present on various platforms and offer various sales channels. One of these options is through their website, which has various functionalities, such as making purchases online without the need to physically visit a physical store. The most important challenges in clothing sales are related to a significant barrier faced by customers who cannot try on clothes as they would in a physical store and do not always have the necessary confidence to make clothing purchases online due to possible inconveniences that may arise, especially if they make mistakes in the size of the garment or if it does not fit as expected. These problems can result in a loss of time and money, due to the necessary logistics for return, which is one of the main barriers to sustainable development of e-commerce in this sector. This paper aims to integrate a body recognition system that, through the capture of two photos, allows it to function as a virtual fitting room and determine the size that the customer should request according to the parameters established by the commerce. The system can be incorporated into any business under the monthly subscription modality. This system will have a maximum margin of error of 2%, which is sufficient to assign and visualize the garment within the established ranges.

Name thesis:degree_name

Ingeniero de Sistemas

Level thesis:degree_level

Título Profesional

Discipline thesis:degree_discipline

Ingeniería de Sistemas

Grantor dc:publisher

Universidad de Lima

Year dc:date.issued

2023

Author dc:creator

• Melgarejo Paucar, Ricardo Antonio

Advisor dc:contributor.advisor

• Saravia Torres, Pedro Humberto

• Reconocimiento de formas
• Industria del vestido
• Pattern perception
• Clothing trade

Statement dc:rights

• info:eu-repo/semantics/openAccess

Licence dc:rights.uri

• https://creativecommons.org/licenses/by-nc-sa/4.0/

Language dc:language.iso

spa

Handle dc:identifier.uri

https://hdl.handle.net/20.500.12724/18832

OAI identifier oai:identifier

oai:repositorio.ulima.edu.pe:20.500.12724/18832