Compressed Animated Light Fields for Real-Time VR Rendering
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Solution Overview
Problem
Current virtual reality (VR) content rendering struggles with real-time cinematic-quality graphics and immersive 360-degree videos, which require high complexity and result in increased authoring, storage, processing, and bandwidth costs due to the need for capturing and rendering from multiple eye locations to prevent immersion breaking and discomfort when viewers diverge from specific eye locations.
Innovation Solution
A computer-implemented method that determines optimal placements for virtual cameras to provide full motion light field visibility, renders the scene, compresses color and depth data, and reconstructs video frames in real-time from compressed data, allowing for real-time rendering from any viewpoint using a pipeline of offline preparation, stream compression, and real-time decompression and reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional VR rendering uses multiple cameras to capture from different eye locations, then immersion and comfort are improved, but device complexity and storage costs increase significantly
Solution Approach 1:
The patent pre-computes camera placements and light field data offline before runtime, storing the results for rapid retrieval during VR playback. This preliminary preparation allows the system to achieve high immersion quality without requiring multiple physical cameras during actual VR operation, as the light field information has already been captured and processed in advance
Solution Approach 2:
The patent creates virtual copies of camera viewpoints through light field reconstruction algorithms. Instead of using multiple physical cameras simultaneously, the system generates synthetic camera views from a single light field dataset, allowing multiple virtual cameras to be instantiated from one physical capture setup, thereby reducing hardware complexity while maintaining immersion quality
2Manufacturing precision
If cinematic-quality graphics are rendered in real-time for VR, then visual fidelity is improved, but processing power and bandwidth requirements increase
Solution Approach 1:
The patent performs computationally intensive rendering operations offline to pre-compute light field data with cinematic quality. By completing the heavy processing work before runtime and storing the results, the system achieves high visual fidelity during VR playback without requiring sustained high processing power, as the data is simply retrieved and displayed in real-time
Solution Approach 2:
The patent replaces real-time mechanical rendering computation with pre-computed light field data retrieval. Instead of continuously calculating complex lighting and geometry interactions during VR playback, the system substitutes these computations with stored light field measurements that were calculated in advance, dramatically reducing real-time processing requirements while maintaining visual quality
3Device complexity
If 360-degree videos are captured from specific eye locations, then capture complexity is reduced, but motion parallax and immersion are lost when viewers diverge
Solution Approach 1:
The patent transitions from capturing 360-degree video at fixed eye locations to capturing light field data that encodes information across multiple spatial dimensions. By measuring light rays from multiple directions and distances simultaneously, the system creates a higher-dimensional representation of the scene that can be viewed from any viewpoint, providing motion parallax and immersion while maintaining manageable capture complexity through specialized optics
Data Source
AI summary
Systems, methods, and articles of manufacture for real-time rendering using compressed animated light fields are disclosed. One embodiment provides a pipeline, from offline rendering of an animated scene from sparse optimized viewpoints to real-time rendering of the scene with freedom of movement, that includes three stages: offline preparation and rendering, stream compression, and real-time decompression and reconstruction. During offline rendering, optimal placements for cameras in the scene are determined, and color and depth images are rendered using such cameras. Color and depth data is then compressed using an integrated spatial and temporal scheme permitting high performance on graphics processing units for virtual reality applications. The compressed content may be decoded and reconstructed in real-time by selecting, using heuristics, cameras that provide useful data for a viewer, selecting grid cells from those cameras that are visible to the viewer, and using a ray marching technique to reconstruct the scene.