3D Data Encoding Using Neighboring Point Prediction
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Solution Overview
Problem
There is a demand for reducing the code amount in encoding three-dimensional data, as existing methods struggle to efficiently compress and transmit large amounts of three-dimensional data.
Innovation Solution
A three-dimensional data encoding method that calculates a new predicted value using attribute information from neighboring points, assigns it to prediction modes, and generates a bitstream including the selected prediction mode and prediction residual.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional encoding methods are used for three-dimensional data, then the data can be stored and transmitted, but the code amount becomes excessively large requiring significant compression
Solution Approach 1:
The patent applies preliminary action by calculating predicted values for attribute information before actual encoding. The encoder predicts attribute values (such as color or reflectance) of current three-dimensional points based on attribute information from neighboring points, and encodes only the residuals (differences between actual and predicted values). This preliminary prediction step reduces the amount of data that needs to be encoded and transmitted, directly addressing the contradiction between code amount and encoding efficiency
Solution Approach 2:
The patent introduces an intermediary mechanism by using predicted values as a mediator between the actual attribute information and the encoded data. Instead of encoding raw attribute information directly, the system uses predicted values derived from neighboring points as an intermediary, encoding only the residuals. This intermediary approach significantly reduces code amount while maintaining encoding efficiency
2Productivity
If the amount of three-dimensional data is reduced through compression, then transmission efficiency improves, but encoding complexity increases
Solution Approach 1:
The patent applies parameter changes by transforming the encoding approach from direct attribute encoding to residual encoding based on predicted values. The system changes the parameter being encoded from raw attribute information to residuals (differences between actual and predicted attributes). This parameter transformation improves transmission efficiency by reducing data volume while managing encoding complexity through systematic prediction algorithms using neighboring point information
Data Source
AI summary
A three-dimensional data encoding method of encoding three-dimensional points includes: calculating a new predicted value as a predicted value, using attribute information items of one or more second three-dimensional points neighboring a first three-dimensional point, and assigning the predicted value to at least one prediction mode among two or more prediction modes, the new predicted value being used for calculating an attribute information item of the first three-dimensional point; selecting one prediction mode from the two or more prediction modes; calculating a prediction residual which is a difference between the attribute information item of the first three-dimensional point and the predicted value of the one prediction mode selected; and generating a bitstream including the one prediction mode and the prediction residual.