18086407. NATURAL AND INTERACTIVE 3D VIEWING ON 2D DISPLAYS simplified abstract (Rovi Guides, Inc.)
Contents
NATURAL AND INTERACTIVE 3D VIEWING ON 2D DISPLAYS
Organization Name
Inventor(s)
Anup Basu of Saint Albert (CA)
NATURAL AND INTERACTIVE 3D VIEWING ON 2D DISPLAYS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18086407 titled 'NATURAL AND INTERACTIVE 3D VIEWING ON 2D DISPLAYS
Abstract: Methods and systems for conversion of imagery and video for three-dimensional (3D) displays, four-dimensional experiences, next-generation user interfaces, virtual reality, augmented reality, mixed reality experiences, and interactive experiences into imagery and video suitable for a two-dimensional (2D) display. A 2D display is configured to generate a 3D-like effect. 3D images are analyzed and represented by parameters including movement, depth, motion, shadow, focus, sharpness, intensity, and color. Using the parameters, the 3D images are converted to 2D images that include the 3D-like effect. The 2D images are presented to users to generate feedback. The feedback informs changes to the conversion. Artificial intelligence systems, including neural networks, are trained for improving the conversion. Models are developed for improving the conversion. Related apparatuses, devices, techniques, and articles are also described.
- Simplified Explanation:
- Conversion of 3D imagery and video into 2D images with a 3D-like effect for display on 2D screens. - Analysis of 3D images using parameters like movement, depth, and color for conversion. - Feedback from users used to enhance the conversion process. - Artificial intelligence systems and neural networks trained to improve the conversion. - Development of models for better conversion results.
- Key Features and Innovation:
- Conversion of 3D content to 2D with a 3D-like effect. - Analysis of 3D images using various parameters. - User feedback loop for improving conversion. - Integration of artificial intelligence for enhanced results. - Development of models to optimize the conversion process.
- Potential Applications:
- Enhancing user experience on 2D displays. - Improving visual quality of 3D content on 2D screens. - Creating immersive experiences for virtual reality and augmented reality applications.
- Problems Solved:
- Bridging the gap between 3D content and 2D displays. - Enhancing the visual appeal of 2D images with a 3D-like effect. - Providing a more engaging viewing experience for users.
- Benefits:
- Improved visual representation of 3D content on 2D screens. - Enhanced user engagement and interaction with converted images. - Potential for new applications in virtual reality and augmented reality technologies.
- Commercial Applications:
- "Enhancing User Experience: Conversion of 3D Imagery for 2D Displays" - Potential applications in gaming, entertainment, advertising, and education sectors. - Market implications include increased demand for 2D displays with 3D-like effects.
- Questions about the Technology:
1. How does the feedback loop from users contribute to improving the conversion process? - The feedback loop helps identify areas for enhancement and refinement in the conversion of 3D imagery to 2D with a 3D-like effect.
2. What role do artificial intelligence systems play in optimizing the conversion of 3D content to 2D images? - Artificial intelligence systems, particularly neural networks, are trained to analyze and process 3D images, leading to improved conversion results.
Original Abstract Submitted
Methods and systems for conversion of imagery and video for three-dimensional (3D) displays, four-dimensional experiences, next-generation user interfaces, virtual reality, augmented reality, mixed reality experiences, and interactive experiences into imagery and video suitable for a two-dimensional (2D) display. A 2D display is configured to generate a 3D-like effect. 3D images are analyzed and represented by parameters including movement, depth, motion, shadow, focus, sharpness, intensity, and color. Using the parameters, the 3D images are converted to 2D images that include the 3D-like effect. The 2D images are presented to users to generate feedback. The feedback informs changes to the conversion. Artificial intelligence systems, including neural networks, are trained for improving the conversion. Models are developed for improving the conversion. Related apparatuses, devices, techniques, and articles are also described.
