Distributed Video Coding Using Reliability Data for Low-Power XR
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Solution Overview
Problem
Current video encoding processes for extended reality (XR) devices are resource-intensive and require complex processors, leading to high energy consumption and latency issues, especially when transmitting high-quality video data over short distances, such as between devices on a person's body.
Innovation Solution
The proposed solution involves a distributed video coding process that shifts some encoding work from the transmitting device to the receiving device, using error correction data to reconstruct missing video data, and applying decimation patterns to reduce the amount of data transmitted, thereby reducing resource consumption and increasing coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex video encoding processes are used to achieve high-quality video transmission, then video quality is improved, but energy consumption and processing complexity increase
Solution Approach 1:
The patent segments the video encoding process into two parts: a simplified encoding process at the transmitting device and a more complex decoding/reconstruction process at the receiving device. This allows the transmitting device to use less energy while maintaining video quality through collaborative processing.
Solution Approach 2:
The patent inverts the traditional encoding paradigm by performing minimal encoding at the transmitter and shifting the computational burden to the receiver. The receiver uses error correction data and prediction algorithms to reconstruct the video, effectively doing the heavy lifting that would traditionally be done at the transmitter.
2Measurement precision
If complex video encoding processes are used to achieve high-quality video transmission, then video quality is improved, but processing complexity increases
Solution Approach 1:
The patent divides the processing complexity between two devices: the transmitting device performs simple encoding while the receiving device handles complex decoding and reconstruction. This segmentation reduces the processor complexity requirement at the transmitting device while maintaining overall video quality.
Solution Approach 2:
The receiving device serves itself by using error correction data and prediction algorithms to reconstruct video data that was minimally encoded. This self-service approach allows the receiver to compensate for the simplified encoding at the transmitter without requiring complex processing at the transmitting end.
3Measurement precision
If all encoded video data is transmitted to ensure complete information, then video reconstruction accuracy is improved, but data transmission volume increases
Solution Approach 1:
The patent extracts only the essential encoded video data for transmission, leaving out redundant information. The receiving device reconstructs the missing video data using error correction codes and prediction algorithms, thereby reducing transmission volume while maintaining reconstruction accuracy.
Solution Approach 2:
The patent introduces error correction data as an intermediary that enables the receiver to reconstruct missing video information. This intermediary data allows for accurate video reconstruction without transmitting all the original encoded data, effectively mediating between reduced transmission volume and maintained reconstruction accuracy.
Data Source
AI summary
A device is configured to generate prediction data for the picture, wherein the prediction data for the picture comprises predictions of blocks of the picture based at least in part on one or more previously reconstructed pictures of the video data; generate encoded video data based on the prediction data for the picture, wherein the encoded video data includes transform blocks that comprises transform coefficients; scale bits of the transform coefficients of the transform blocks based on reliability values for bit positions; generate error-corrected encoded video data using the error correction data to perform an error correction operation on the scaled bits of the transform coefficients of the transform blocks; and reconstruct the picture based on the error-corrected encoded video data.