Polygon Mesh Encoding via Adaptive Vertex Traversal
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Solution Overview
Problem
Existing methods for encoding and decoding visual content, particularly polygon meshes, are inefficient in terms of resource utilization and latency, as they do not effectively optimize the traversal order of vertices and encoding of triangle groups, leading to larger data streams and increased computational and storage requirements.
Innovation Solution
A method that involves traversing the vertices of a polygon mesh based on adaptive traversal orders determined by the number of previously encoded triangles or the sum of angles formed by these triangles, partitioning triangles into ordered groups, and encoding these groups using a set of predefined templates, thereby reducing data size and processing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional encoding methods are used for polygon meshes, then the encoding process is simple, but the data stream size is large and resource utilization is inefficient
Solution Approach 1:
The patent segments the polygon mesh encoding process into distinct phases: vertex traversal with priority assignment, triangle group identification, template selection, and coefficient encoding. This segmentation allows each component to be optimized independently, reducing overall data stream size while maintaining manageable complexity through structured processing
Solution Approach 2:
The patent performs preliminary actions by pre-defining a set of templates that represent common triangle group configurations. During encoding, the system identifies which template best matches each triangle group and encodes only the template identifier and deviation coefficients, rather than encoding complete triangle data, significantly reducing data stream size
2Productivity
If adaptive traversal order based on triangle count or angle sum is used, then encoding efficiency improves, but computational complexity increases
Solution Approach 1:
The patent changes the traversal parameter from a fixed or arbitrary order to an adaptive order based on calculated parameters such as the number of incident triangles or the sum of angles at each vertex. This parameter change enables the encoder to prioritize vertices that will lead to more compact triangle groupings, improving encoding efficiency while the computational overhead is managed through efficient algorithms
Solution Approach 2:
The system uses feedback from the mesh structure itself (triangle connectivity and angular relationships) to dynamically determine the optimal traversal order. By analyzing the actual geometric properties of the input mesh, the encoder adapts its traversal strategy to match the specific characteristics of each mesh, improving efficiency without requiring overly complex preprocessing
3Quantity of substance
If triangles are partitioned into ordered groups using templates, then data compression improves, but decoding complexity increases
Solution Approach 1:
The patent uses template copying where common triangle group patterns are represented by predefined template identifiers. Instead of encoding each triangle's complete geometric data, the system copies the template structure and only encodes the specific coefficients that deviate from the template, achieving high compression while keeping decoding straightforward through template matching
Solution Approach 2:
The patent groups homogeneous triangle configurations together under common templates. By identifying and encoding groups of triangles that share similar geometric characteristics using the same template, the system achieves better compression ratios while the decoder can efficiently reconstruct these homogeneous groups through simple template instantiation
4Loss of time
If vertex traversal is optimized based on incident triangles and angles, then latency is reduced, but processing resources increase
Solution Approach 1:
The patent performs preliminary computation of vertex priorities based on incident triangle counts and angle sums before the actual traversal begins. This preliminary action allows the optimized traversal order to be established once, reducing latency during the main encoding process while the computational cost is amortized over the entire encoding operation
Solution Approach 2:
The patent segments the resource-intensive computations into distinct phases: priority calculation, traversal execution, and template matching. By separating the computationally heavy priority calculation from the traversal and encoding phases, the system can optimize each segment independently, reducing overall latency while managing processing resources more efficiently
Data Source
AI summary
According to an example method, a system receives first data representing a polygon mesh. The polygon mesh includes a plurality of interconnected vertices forming a plurality of triangles. The system generates second data representing the polygon mesh. Generating the second data includes traversing the vertices of the polygon mesh according to a traversal order, partitioning the plurality of triangles into a set of ordered triangle groups in accordance with the traversal order, and encoding, in the second data, the set of ordered triangle groups. The system outputs the second data. A position each of the vertices in the transversal order is determined based on (i) a number of previously encoded triangles that are incident to that vertex, and/or (ii) a sum of one or more angles formed by the previously encoded triangles that are incident to that vertex.