Real-Time 3D Video Panoramic Rendering via Spherical Model Segmentation
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Solution Overview
Problem
Existing methods for panoramic rendering of 3D videos require processing all frame images beforehand, preventing real-time playback.
Innovation Solution
A method that determines the image format of a 3D video based on video information, generates spherical models for left and right eyes, and renders each frame in real-time using angle-of-view rotation and image scaling data, allowing for panoramic real-time playback by outputting images to a display device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If all frame images are processed beforehand, then rendering quality is improved, but real-time playback capability deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-generating spherical models and establishing the rendering framework before actual video playback. The spherical models are created in advance with proper coordinate systems and mapping relationships, but the actual frame-by-frame rendering is performed in real-time during playback, combining pre-computation of structural elements with real-time processing of content data.
2Manufacturing precision
If complex spherical model rendering is performed, then panoramic rendering quality is improved, but device compatibility and operation ease deteriorate
Solution Approach 1:
The patent segments the panoramic rendering process into distinct components: separate spherical models for left and right eyes, independent sub-image processing, and modular coordinate transformation functions. This segmentation allows each component to be optimized independently and facilitates deployment across different device platforms with varying computational capabilities.
Solution Approach 2:
The patent employs parameter changes by utilizing angle-of-view rotation data and image scaling data to dynamically adjust rendering parameters. The spherical models are rendered with adjustable viewing angles and scale factors, allowing the same base model to adapt to different display devices and user preferences without requiring device-specific model creations.
Data Source
AI summary
A method is provided. The method includes: reading video information of a 3D video to be rendered; determining an image format of the 3D video according to the video information; generating a first spherical model and a second spherical model according to the image format; reading a frame image of the 3D video, where the frame image includes a first sub-image and a second sub-image; obtaining angle-of-view rotation data and image sealing data; rendering the frame image according to the angle-of-view rotation data and the image scaling data, where the first sub-image is rendered to the first spherical model to obtain a first spherical image, and the second sub-image is rendered to the second spherical model to obtain a second spherical image; and outputting images in a viewport area of the first spherical image and the second spherical image to a display device.