Atlas Hash Verification for Video Decoding Error Detection
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Solution Overview
Problem
In immersive video coding and point cloud coding standards like V3C/V-PCC and MIV, there is a need to confirm that decoders are obtaining unaltered and correctly decoding bitstreams, as current methods lack effective verification for decoding errors.
Innovation Solution
Implementing a supplemental enhancement information (SEI) message with an atlas data hash to verify the integrity of decoded data by comparing encoder-side and decoder-side hash values of the atlas data, ensuring compliance with coding standards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video compression is increased to improve bandwidth efficiency, then compression efficiency improves, but video quality deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the encoder generates a hash value of the atlas data and transmits it to the decoder. The decoder independently generates the same hash value from the decoded atlas data and compares it with the received hash value. This feedback loop enables automatic detection of decoding errors without requiring manual quality assessment, allowing the system to maintain high compression ratios while ensuring video quality through automated verification.
2Speed
If current verification methods are used, then decoding speed is maintained, but decoding error detection capability deteriorates
Solution Approach 1:
The patent replaces complex mechanical verification methods (such as full frame-by-frame visual inspection or sophisticated error correction algorithms) with a simple hash-based verification mechanism. By substituting the verification process with a lightweight hash comparison operation, the system maintains high decoding speed while significantly improving error detection capability. The hash computation is computationally efficient and can be performed rapidly without bottlenecking the decoding pipeline.
3Reliability
If hash verification is implemented to improve decoding error detection, then reliability improves, but device complexity increases
Solution Approach 1:
The patent extracts only the essential verification information (hash value) from the complex atlas data and transmits it separately as supplemental enhancement information (SEI). This extraction approach allows the system to implement comprehensive verification without increasing overall system complexity, as only a small amount of hash data needs to be transmitted and processed. The core verification logic is simplified to hash generation and comparison operations, avoiding the need for complex verification infrastructure.
4Measurement precision
If comprehensive verification of decoded data is implemented, then measurement precision improves, but loss of information increases due to additional data transmission
Solution Approach 1:
The patent transforms the verification approach by changing the parameter representation from transmitting raw atlas data or detailed verification information to transmitting a compressed hash value. This parameter change dramatically reduces the amount of data that needs to be transmitted for verification purposes. The hash function converts large amounts of atlas data into a compact fixed-size value, enabling comprehensive verification with minimal bandwidth consumption for the verification data itself.
Data Source
AI summary
Methods, apparatus, systems and articles of manufacture to identify a video decoding error are disclosed. An example apparatus includes an atlas generator to generate atlas data for one or more atlases generated from input views of video; a hash generator to: perform a hash operation on the atlas data to generate a hash value; and include the hash value in a message; and a multiplexer to combine the one or more atlases, coded atlas data corresponding to the atlas data, and the message to generate a video bitstream.