Samsung electronics co., ltd. (20240346765). METHOD AND AN ELECTRONIC DEVICE FOR 3D SCENE RECONSTRUCTION AND VISUALIZATION simplified abstract
Contents
METHOD AND AN ELECTRONIC DEVICE FOR 3D SCENE RECONSTRUCTION AND VISUALIZATION
Organization Name
Inventor(s)
Anna Ilyinichna Sokolova of Moscow (RU)
Anna Borisovna Vorontsova of Moscow (RU)
Alexander Georgievich Limonov of Moscow (RU)
METHOD AND AN ELECTRONIC DEVICE FOR 3D SCENE RECONSTRUCTION AND VISUALIZATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240346765 titled 'METHOD AND AN ELECTRONIC DEVICE FOR 3D SCENE RECONSTRUCTION AND VISUALIZATION
Simplified Explanation: The patent application describes a method for reconstructing and visualizing 3D scenes using neural networks and algorithms.
Key Features and Innovation:
- Training a neural network to obtain distance information for voxels in a real scene.
- Using the trained network to analyze input frames and reconstruct a 3D scene.
- Rendering the reconstructed scene for visualization.
- Displaying the 3D visualization on a display.
Potential Applications: This technology can be used in various fields such as virtual reality, augmented reality, gaming, and architectural visualization.
Problems Solved: This method addresses the challenge of accurately reconstructing 3D scenes from 2D images or video frames.
Benefits:
- Accurate and detailed 3D scene reconstruction.
- Realistic visualization of scenes.
- Potential for immersive experiences in VR and AR applications.
Commercial Applications: The technology can be applied in industries such as entertainment, architecture, gaming, and simulation for enhanced visualization and user experience.
Prior Art: Researchers can explore prior work on neural network-based scene reconstruction and visualization techniques in computer vision and graphics literature.
Frequently Updated Research: Stay updated on advancements in neural network training methods, 3D reconstruction algorithms, and real-time visualization techniques for 3D scenes.
Questions about 3D Scene Reconstruction and Visualization: 1. How does this technology improve the accuracy of 3D scene reconstruction compared to traditional methods? 2. What are the potential limitations of using neural networks for scene reconstruction and visualization?
Original Abstract Submitted
a method for 3d scene reconstruction and visualization, may include, using at least one processor: obtaining a trained base neural network by training the base neural network for obtaining distance information for voxels of a real scene; operating the trained base neural network for obtaining the distance information of an input sequence of frames of the real scene; inputting the distance information to an algorithm that outputs a 3d reconstruction of the real scene; obtaining a 3d visualization of the real scene by rendering the 3d reconstruction of the real scene; and instructing at least one display to display the 3d visualization of the real scene.
