Snap inc. (20240303843). DEPTH ESTIMATION FROM RGB IMAGES simplified abstract
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DEPTH ESTIMATION FROM RGB IMAGES
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Inventor(s)
DEPTH ESTIMATION FROM RGB IMAGES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240303843 titled 'DEPTH ESTIMATION FROM RGB IMAGES
- Simplified Explanation:**
This patent application describes a system that uses image data of hands and a depth estimation model to generate extended reality effects for users during an extended reality experience.
- Key Features and Innovation:**
- Utilizes image data of hands in a real-world scene
- Trains a depth estimation model using synthetic 2D image data with sets of depths and segmentation masks
- Generates extended reality effects using the image data and depth estimation model
- Potential Applications:**
- Virtual reality gaming
- Augmented reality applications in education
- Training simulations for various industries
- Medical training and visualization
- Problems Solved:**
- Enhances user experience in extended reality environments
- Improves realism and immersion in virtual and augmented reality applications
- Enables more accurate depth perception in extended reality experiences
- Benefits:**
- Enhanced user engagement and interaction
- Improved visual quality and realism in extended reality content
- More accurate depth perception for users
- Commercial Applications:**
- "Enhanced Extended Reality Effects System for Immersive Experiences"
- Potential applications in gaming, education, training, and healthcare industries
- Market implications include increased demand for extended reality content and experiences
- Prior Art:**
There may be prior art related to depth estimation models and extended reality effects using hand image data. Researchers and developers in the field of computer vision and augmented reality may have explored similar technologies.
- Frequently Updated Research:**
Researchers may be continuously improving depth estimation models and exploring new ways to enhance extended reality effects using hand image data.
- Questions about Extended Reality Effects System:**
1. How does the system accurately estimate depths from hand image data? 2. What are the potential limitations of using synthetic 2D image data for training the depth estimation model?
Original Abstract Submitted
a system for generating extended reality effects using image data of hands and a depth estimation model. the depth estimation model is trained using pairings of synthetic 2d image data with sets of depths and segmentation masks. an extended reality system captures image data of hands in a real-world scene and uses the image data and the depth estimation model to generate the extended reality effects. the extended reality effects are provided to a user during an extended reality experience.
