LayOut Loud: An AI-Powered Augmented Reality and Mobile Application for Room Interior Design and Layout Optimization
LayOut Loud is an AI-powered augmented reality (AR) and mobile application designed to revolutionize room interior design by offering tailored, real-time solutions for layout optimization. The primary objective of this tool is to design AI-powered features that analyze user-provided room dimensions, furniture types, and style preferences. By leveraging advanced algorithms, LayOut Loud generates personalized design suggestions that cater to the individual needs and aesthetic tastes of users, ensuring that each interior design experience is customized and unique. A key goal of the application is to enhance user experience and decision-making through a clustering algorithm. This algorithm categorizes furniture pieces based on their suitability and appearance in living spaces, streamlining the selection process for users. By enabling the visualization of these items in a 3D model, users can make informed decisions about their interior design choices, ensuring that each piece contributes to the overall aesthetic and functional harmony of the space. Additionally, LayOut Loud focuses on improving its AR capabilities by allowing users to capture their room layouts and view virtual furniture arrangements in real time. This feature provides practical, interactive design solutions, empowering users to experiment with different configurations and instantly see how potential changes would appear in their actual living environments. Ultimately, LayOut Loud offers a user-friendly, immersive platform that transforms the way individuals approach interior design.
Authors
- Vivien A. Agustin (ORCID: https://orcid.org/0000-0001-7357-3596)
- Criselle J. Centeno
- Richard C. Regala (ORCID: https://orcid.org/0000-0002-8475-4736)
- Alfredo Santillán (ORCID: https://orcid.org/0000-0001-9823-7396)
- J. Cuevas
- Mary Grace N. Gonzales
- John Kenneth R. Rili
Institutions
- University of the City of Manila (PH)
Publication Details
- Published
- 2024-12-17
- DOI
- https://doi.org/10.1109/icicyta64807.2024.10912928
- Citations
- 4
- Primary Topic
- Augmented Reality Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.00