3D Surface Data Compression via 2D Image Tiling
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Solution Overview
Problem
Current compression techniques for 3D surface data are incompatible with common image compression algorithms, making it difficult to achieve efficient compression and decompression for 3D objects, especially in global digital spaces, and fail to provide an interactive and engaging experience.
Innovation Solution
The method involves decomposing surface data into oriented bounding boxes, transforming them into canonical camera representations, converting into grayscale and color image pairs, tiling these images, and using image encoders like PNG, JPEG, or TIFF to compress the data, allowing for compatible compression and decompression with existing image data algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If mesh parameterization with multiple vertices and edges is used for accurate surface representation, then manufacturing precision is improved, but device complexity increases and ease of manufacture deteriorates
Solution Approach 1:
The patent segments the 3D surface data into multiple 2D image tiles that can be independently processed. Each tile represents a portion of the surface and can be encoded separately using standard image codecs, avoiding the need for a single complex mesh encoder while maintaining accurate surface representation through the collection of segmented tiles.
Solution Approach 2:
The patent introduces 2D image tiles as an intermediary representation between the 3D surface data and the final encoded output. This intermediary format allows standard image compression algorithms to be applied, bridging the gap between accurate 3D surface representation and compatibility with existing encoding infrastructure.
2Device complexity
If mesh decimation techniques are applied to reduce vertices, then device complexity is reduced, but manufacturing precision deteriorates
Solution Approach 1:
The patent creates 2D image copies or projections of the 3D surface data that can be encoded independently. These image copies serve as simplified representations that capture essential surface information without requiring complex mesh structures, enabling use of standard encoders while preserving sufficient visual fidelity.
3Manufacturing precision
If customized encoders are used for 3D surface data, then manufacturing precision is improved, but adaptability deteriorates
Solution Approach 1:
The patent transforms 3D surface data into 2D image representations, changing the dimensional domain of the data. This dimensionality change allows standard 2D image compression algorithms to be applied effectively, achieving good compression results without requiring specialized 3D encoders, thus improving compatibility and adaptability.
Solution Approach 2:
The patent makes the encoding system universal by using standard image codecs that can handle multiple types of image data. The same encoding infrastructure used for photographs and graphics can now also compress 3D surface data, eliminating the need for proprietary encoders and improving versatility across different platforms and devices.
4Ease of manufacture
If 2D data compression is used, then ease of manufacture is improved, but manufacturing precision deteriorates
Solution Approach 1:
The patent segments the 3D surface into multiple 2D image tiles that can be independently compressed using standard algorithms. By dividing the surface into manageable 2D portions, the patent achieves ease of implementation with existing tools while maintaining overall 3D surface accuracy through the collective representation of all tiles.
Data Source
AI summary
A processor implemented method for compressing surface data of a 3 dimensional object in a global digital space, using an image encoder that supports an image data compression algorithm, the image encoder being coupled to a transmitter. The method includes the steps of (i) decomposing the surface data into at least one surface representation that is encoded in an oriented bounding box, (ii) transforming the oriented bounding box into a canonical camera representation to obtain canonical coordinates for the at least one surface representation, (iii) converting each of the at least one surface representation into at least one bounding box image pair that includes a grayscale image representing depth, and a color image and (iv) tiling the at least one bounding box image pair to produce a tiled bounding box image.