Examinando por Materia "Realidad aumentada"
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Ítem Actitudes de los bogotanos en el uso de realidades mixtas : realidades virtual y aumentada(Universidad EAFIT, 2020) Yepes Rios, Juan David; Ortiz Uribe, Sandra Milena; Rojas de Francisco, Laura IsabelÍtem The Earth in your hands(Universidad EAFIT, 2023) Cárdenas Franco, Luis Alejandro; Vásquez Arias, Mauricio; Colorado Chávez, Paula Andrea; Montoya Estrada, Alejandra; Ospina Lopera, Mónica Liliana; Serna Salazar, Natalia; Universidad EAFITDigital experience with a narrative approach that promotes care and respect for biodiversity. It uses an environment designed to be visualized in augmented reality, showing what the La Volcana stream would look like in the future if its architectural spaces were more inhabited by fauna and flora.Ítem Implementation of conceptual validation of product mock ups with augmented reality(2012) Osorio Gómez, Gilberto; Mejía Gutiérrez, Ricardo; Ríos Zapata, David; Universidad EAFIT. Departamento de Ingeniería de Diseño; Ricardo Mejia (rmejiag@eafit.edu.co); Gilberto Osorio (gosoriog@eafit.edu.co); David Rios (drioszap@eafit.edu.co); Ingeniería de Diseño (GRID)The implementation of computational aids in product design is a demand in the design processes on century XXI, that because they allow an increase in quality and creativity of the deliverables of a design process -- But this implementation should be guided to an academic process, where technologies methodologies work along -- This article presents the results of an implementation of virtual reality techniques to validate and increased product design courses within the undergraduate electrical mobility in Product Design Engineering at that universityÍtem Influencia de la realidad aumentada en las decisiones de compra de prendas de vestir en comercios electrónicos(Universidad EAFIT, 2021) Valderrama Henao, Martha Liliana; Muñoz Molina, Yaromir de JesúsThis thesis focused on the potential of augmented reality in the fashion retail, which has been poorly researched in Colombia. This time we wanted to show how this technology has been used to deliver brand experiences and show the innovative and technological side of companies when selling and facilitating the purchase of clothing to users, whether or not you can influence purchasing decisions in e-commerces. Likewise, what have been the challenges and limitations for companies that have used augmented reality, those that have developed this technology, as it is expected to be a new channel of communication between customers and companies. The method used to develop this research was mixed type, in which were interviewed developers of augmented reality, companies in the fashion sector that have used this technology and, finally, a questionnaire was carried out to 279 people to know if augmented reality could influence their decision to buy in e-commerce channels, which allowed to show that the ease of use , the realism and the user's ability to deduction when having an application are the features in which everyone agrees must have such an application. In addition, knowing the benefits of augmented reality from a marketing point of view, bearing in mind that it is a digital trend, which encourages future students to conduct similar research. From this research is concluded, among others, that pandemic gave a turn to the retail trade in how much to use more online channels, less use of clothing, payment with QR codes, where augmented reality will be an ally for this type of experiences, although it is an expensive technology, the recommendation is to carry out joint efforts so retail companies can have their own market place or their own applications to give the best user experience.Ítem El Metaverso generalidades y conceptos para su implementación(Universidad EAFIT, 2023) Gómez Mora, Óscar Julián; Uribe de Correa, Beatriz AmparoÍtem On object recognition for industrial augmented reality(Universidad EAFIT, 2018) Arbeláez, Juan Carlos; Osorio Gómez, Gilberto; Viganó, RobertoSome reasons are market pressure, an increase of functionality, and adaptability to an already complex environment, among others. Therefore, workers face fast-changing and challenging tasks along with all the product lifecycle that reach the human cognitive limits. Although nowadays some operations are automated, many of them still need to be carried out by humans because of their complexity. In addition to management strategies and design for X, Industrial Augmented Reality (IAR) has proven to potentially benefit activities such as maintenance, assembly, manufacturing, and repair, among others. It is also supposed to upgrade the manufacturing processes by improving it, simplifying decision-making activities, reducing time and user movements, diminishing errors, and decreasing mental and physical effort. Nevertheless, IAR has not succeeded in breaking out of the laboratories and establishing itself as a strong solution in the industry, mainly because technical and interaction components are far from ideal. Its advance is limited by its enabling technologies. One of its biggest challenges are the methods for understanding the surroundings considering the different domain variables that affect IAR implementations. Thus, inspired by some systematical methodologies proposing that, for any problemsolving activity, it is required to define the characteristics that constrain the problem and the needs to be satisfied, a general frame of IAR was proposed through the identification of Domain Variables (DV), that are relevant characteristics of the industrial process in the previous Augmented Reality (AR) applications. These DV regard the user, parts, environment, and task that have an impact on the technical implementation and user performance and perception (Chapter 2). Subsequently, a detailed analysis of the influence of the DV on technical implementations related to the processes intended to understand the surroundings was performed. The results of this analysis suggest that the DV influence the technical process in two ways. The first one is that they define the boundaries in the characteristics of the technology, and the second one is that they cause some issues in the process of understanding the surroundings (Chapter 3). Further, an automatic method for creating synthetic datasets using solely the 3D model of the parts was proposed. It is hypothesized that the proposed variables are the main source of visual variations of an object in this context. Thus, the proposed method is derived from physically recreated light-matter interactions of this relevant variables. This method is aimed to create fully labeled datasets for training and testing surrounding understanding algorithms (Chapter 4). Finally, the proposed method is evaluated in a study case of object classification of two cases: a particular industrial case, and a general classification problem (using classes of ImageNet). Results suggest that fine-tuning models with the proposed method reach comparable performance (no statistical difference) than models trained with photos. These results validate the proposed method as a viable alternative for training surrounding understanding algorithms applied to industrial cases (Chapter 5).