Volumetric Video Texture Timecode Embedding
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Solution Overview
Problem
Existing methods for streaming volumetric video over the web face challenges in achieving real-time, low-latency delivery due to the large amount of data required, leading to long loading times and interrupted user experiences.
Innovation Solution
A volumetric video processing system and method that embeds a timecode into the texture of each frame, allowing for efficient streaming by enabling the loading of only the necessary frames near the current timecode, thereby reducing data transfer and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all frames of volumetric video are loaded for streaming, then complete video content is available, but data transfer volume increases and latency increases
Solution Approach 1:
The patent segments the volumetric video data by embedding timecodes into individual frame textures, allowing the streaming system to divide and transmit only the specific time-range frames that are currently needed, rather than loading all frames. This segmentation enables selective frame transmission and reduces overall data transfer volume.
Solution Approach 2:
The timecode is embedded into each frame texture in advance during video encoding, creating a pre-indexed structure. This preliminary action allows the streaming system to quickly identify and retrieve only the necessary frames based on current playback time without having to scan or load unnecessary data, thereby reducing latency.
2Productivity
If frame data is compressed to reduce data transfer, then transmission efficiency improves, but decoding complexity and processing time increase
Solution Approach 1:
The patent merges the timecode information directly into the frame texture data structure, combining indexing information with the visual content. This merging eliminates the need for separate index files or metadata structures, simplifying the overall data structure and reducing processing complexity during streaming and playback.
Solution Approach 2:
Each frame texture contains its own embedded timecode, making the data self-describing and self-identifying. This self-service approach allows the streaming system to automatically identify and retrieve required frames without external indexing or complex query mechanisms, reducing server-side processing complexity.
Data Source
AI summary
A volumetric video processing system and method is provided. The volumetric video processing system includes a storage circuit and a processor. The storage circuit is configured to storing a program code. The processor is coupled to the storage circuit and accessing the program code to execute: obtaining a texture of a frame of a volumetric video; generating a timecode based on a frame number of the frame; embedding the timecode into the texture to generate an embedded texture; obtaining a 3D model of the frame; and storing the embedded texture and the 3D model together as the volumetric video.