Atlas Frame Video Encoding for VR Redundancy
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Solution Overview
Problem
Conventional video encoding techniques are inadequate for efficiently encoding video content that forms part of a three-dimensional virtual reality scene, leading to inefficiencies in data processing and user experience, especially in systems with limited resources.
Innovation Solution
A video encoding system that accesses synchronized color and depth data images, performs a first-pass encoding by identifying motion vector data for color images and leverages this data for depth images, and conducts a second-pass encoding to create separate color and depth video streams, optimizing processing and reducing redundancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional video encoding techniques are used on virtual reality video data, then the encoding process is simpler, but the encoding efficiency is insufficient and redundant processing occurs
Solution Approach 1:
The patent divides the video data into multiple layers including base layer video data and enhancement layer video data. The base layer contains essential visual information while the enhancement layer contains additional details. This segmentation allows the encoder to process different layers with appropriate complexity, improving overall encoding efficiency without unnecessarily complicating the entire encoding process.
Solution Approach 2:
The patent applies different encoding strategies to different parts of the video data. The base layer receives more rigorous encoding to ensure quality, while the enhancement layer can use more aggressive compression. Motion vector data is selectively applied to different layers with varying intensity, optimizing resource usage and reducing redundant processing while maintaining overall video quality.
2Measurement precision
If motion vector data from color images is processed separately for depth images, then processing accuracy is maintained, but redundant processing increases and network impact worsens
Solution Approach 1:
The patent merges the motion vector data from color images with the depth images. Instead of independently encoding motion vectors for both color and depth streams, the system utilizes the motion vector data derived from color images to guide the encoding of depth images. This combining approach maintains measurement precision for depth motion estimation while significantly reducing the total amount of data that needs to be transmitted over the network.
Solution Approach 2:
The patent copies motion vector data from the color image stream and applies it to the depth image stream. Rather than calculating completely new motion vectors for depth images, the system copies and adapts the motion information already extracted from color images. This approach preserves the accuracy of motion estimation while avoiding redundant calculation and reducing network bandwidth consumption by transmitting a unified or reduced set of motion vector data.
Data Source
AI summary
An exemplary image generation system accesses a full atlas frame sequence that incorporates a set of image sequences combined within the full atlas frame sequence as atlas tiles. The system generates a first partial atlas frame sequence that incorporates a first subset of image sequences selected from the set of image sequences incorporated in the full atlas frame sequence, as well as a second partial atlas frame sequence that incorporates a second subset of image sequences selected from the set of image sequences. The second subset includes a different combination of image sequences than the first subset and includes at least one image sequence in common with the first subset. The system provides the first partial atlas frame sequence to a first video encoder and the second partial atlas frame sequence to a second video encoder communicatively coupled with the first video encoder. Corresponding methods and systems are also disclosed.