Information Processing for NFT-Linked Volumetric Content Valuation
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Solution Overview
Problem
There is a demand for providing digital content generated using volumetric capture technology while protecting the rights of creators, but evaluating the value of such content linked with an NFT has not been easy.
Innovation Solution
An information processing apparatus links a non-fungible token (NFT) to digital content generated from volumetric capture data, estimates its value based on static and dynamic evaluations, and manages trading through a blockchain system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If digital content is generated using volumetric capture technology and linked with NFT, then creator rights protection is improved, but value evaluation difficulty increases
Solution Approach 1:
The value evaluation system is segmented into two independent components: static evaluation (assessing inherent content quality, rarity, and creator reputation) and dynamic evaluation (tracking market transactions, ownership history, and usage data). This segmentation allows each component to be evaluated separately using appropriate methodologies, resolving the difficulty of comprehensive value assessment while maintaining creator rights protection through the blockchain-linked NFT system.
Solution Approach 2:
The patent introduces an intermediary information processing apparatus that acts as a mediator between the digital content, NFT system, and market participants. This intermediary automatically performs value evaluations by collecting data from multiple sources, processing it through established algorithms, and providing objective valuation reports. This resolves the evaluation difficulty by replacing subjective human assessment with an automated intermediary system that operates transparently and consistently.
2Measurement precision
If static and dynamic evaluations are combined for value estimation, then evaluation accuracy is improved, but system complexity increases
Solution Approach 1:
The system employs dynamic weighting factors that automatically adjust the contribution of static versus dynamic evaluation components based on market conditions, content type, and data availability. For example, newly minted NFTs may rely more heavily on static evaluation, while established assets incorporate more dynamic market data. This dynamic adaptation improves evaluation accuracy without requiring manual system reconfiguration, managing complexity through automated parameter adjustment.
Solution Approach 2:
The system incorporates feedback loops where evaluation results are continuously monitored and used to refine evaluation algorithms. Market transactions and ownership changes provide feedback that adjusts the weighting between static and dynamic components over time. This self-regulating feedback mechanism improves accuracy by adapting to changing market conditions while maintaining system complexity at manageable levels through automated learning rather than manual intervention.
Data Source
AI summary
An information processing apparatus is provided. The apparatus sets information indicating a static evaluation of digital content. The digital content is generated on the basis of three-dimensional shape data indicating a three-dimensional shape of a subject generated using a plurality of captured images obtained by a plurality of image capturing apparatuses. The static evaluation is an evaluation of substance of the digital content. The apparatus determines a dynamic evaluation of the digital content. The dynamic evaluation is an evaluation that can change over time. The apparatus estimates a value of the digital content on the basis of both the static evaluation and the dynamic evaluation.