3D Model Attribute Encoding via Spiral Path Mapping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current 3D model compression algorithms do not effectively utilize correlations between vertices, leading to unsatisfactory coding efficiency for encoding and decoding attribute values in 3D objects.
Innovation Solution
A method involving a spiral-like scanning path to map attribute values onto a 2D image, where the path is split into segments and assigned to lines or columns, allowing for efficient encoding and decoding using image or video encoders/decoders, while maintaining spatial correlations between vertices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional compression algorithms are used to encode attribute values in 3D models, then the encoding process is simple, but the coding efficiency is unsatisfactory
Solution Approach 1:
The patent transforms the 3D model attribute values into a 2D image representation by mapping vertices along a spiral scanning path to 2D image pixels. This dimensional transformation allows the use of efficient 2D image compression algorithms to encode the attribute data, significantly improving coding efficiency while maintaining a manageable encoding process
Solution Approach 2:
The patent divides the spiral scanning path into multiple segments and assigns each segment to specific lines or columns in the 2D image. This segmentation approach maintains spatial correlations within segments while enabling efficient processing and encoding of the transformed data
2Reliability
If attribute values are mapped to 2D image using spiral scanning path, then spatial correlations are maintained, but data transformation complexity increases
Solution Approach 1:
The patent performs the spiral scanning path transformation and 2D image mapping as a preliminary step before encoding. By pre-organizing the attribute data into a 2D structure that preserves spatial correlations, the subsequent encoding process becomes more efficient without requiring complex real-time transformations during compression
3Measurement precision
If more data is used to represent 3D models, then encoding precision is improved, but bitstream size increases
Solution Approach 1:
The patent changes the representation parameters by transforming 3D vertex attribute data into a 2D image format. This parameter transformation enables the application of 2D compression techniques that achieve higher precision in representing attribute values while reducing the overall bitstream size through efficient encoding of the transformed data structure
Data Source
AI summary
Encoding and decoding of property data, such as colour values, associated with vertices forming 3D objects. From an analysis of connectivity data, a spiral-like scanning path of the vertices within the 3D model is obtained. The colour values are mapped to a 2D image, each attribute value to a pixel. Next, the mapped 2D image is encoded. To increase redundancies in the 2D image, the spiral-like path is split into path segments, each forming a turn in the spiral; each path segment is assigned to a respective line of the 2D image; and the colour values of each path segment are mapped, in the same order, to the respective line of the 2D image. Successive lines in the 2D image thus contain the colour values of neighbouring vertices in the 3D object, and a better encoding can be achieved.