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An Indoor Design Assistance System Integrating Depth Sensors and Computer Graphics

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Publicado en:International Journal of E-Collaboration vol. 21, no. 1 (2025), p. 1-17
Autor principal: Wu, Feng
Otros Autores: Tang, Wen
Publicado:
IGI Global
Materias:
Universal design
Accuracy
Data collection
Collaboration
User experience
Adaptability
Sensors
Reinforcement
Machine learning
Optimization
Interdisciplinary aspects
Efficiency
Data integration
Computer graphics
Intelligent design
Feedback
Visualization
Intelligence
Spatial data
Transformation
Artificial intelligence
Modular systems
Interior design
Algorithms
Customization
Real time
Design optimization
Multisensor fusion
Semantics
Acceso en línea:Citation/Abstract
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Resumen:Facing the dual challenges of growing personalized demands and efficiency improvements in the indoor design industry, this paper proposes an intelligent design assistance system that integrates depth sensors with computer graphics. This system achieves automated spatial data collection through multimodal data fusion technology, constructs immersive design environments with real-time rendering engines, and optimizes spatial layouts using reinforcement learning algorithms. Research results verify the system's significant advantages in enhancing design efficiency, optimizing spatial quality, and enhancing user experience, providing critical technological support for promoting digital transformation within the indoor design industry. The system's modular architecture enables seamless integration with existing design workflows, ensuring adaptability to diverse project requirements and client preferences.
ISSN:1548-3673
1548-3681
DOI:10.4018/IJeC.389057
Fuente:ABI/INFORM Global