Dynamic Backfilling 3D Point Cloud Gaps
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Solution Overview
Problem
Existing methods for addressing gaps and discontinuities in 3D point clouds when zooming in, such as increasing point size or adding points based on averages, often degrade image quality by altering the shape and texture of surfaces.
Innovation Solution
Dynamic backfilling using a graphics system that models textures, contours, and patterns of surfaces to generate new points that match the original surface characteristics, employing neural networks like NeRF to create continuous surfaces without distorting the original shape or texture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the size of points is increased to reduce spacing between points when zooming in, then the gaps become less visible, but the image quality degrades due to pixelated or blocky appearance and inaccurate rendering
Solution Approach 1:
The system pre-calculates and stores additional point positions and properties in a lookup structure during an offline processing stage. When rendering, these pre-computed points are retrieved and inserted into gaps between existing points, allowing continuous surface generation without degrading original point characteristics or requiring real-time computational heavy operations.
Solution Approach 2:
The system creates copies of existing points by interpolating new point positions and properties (color, material, etc.) between neighboring points. These copied points are then inserted into gaps to fill discontinuities while maintaining the visual characteristics of the original surface, avoiding the need to enlarge original points which would cause pixelation.
2Reliability
If new points are added based on averaging positions and color values of neighboring points to plug gaps, then visual continuity is restored, but the texture and shape of surfaces are distorted
Solution Approach 1:
Instead of using a uniform averaging approach, the system applies different interpolation methods and weights to different regions based on their local characteristics. Points closer to the gap center are given higher weight, and the interpolation parameters are adjusted according to the specific surface properties (texture, curvature, material) detected in neighboring regions, preserving local surface accuracy while filling gaps.
Solution Approach 2:
The system dynamically adjusts interpolation parameters such as the number of neighboring points to consider, the weighting factors, and the interpolation method based on the local point cloud density and surface characteristics. This adaptive parameter adjustment allows gap filling that respects the original surface geometry and texture patterns rather than imposing a generic averaged solution.
Data Source
AI summary
Disclosed is a graphics system and associated methods for dynamic backfilling a point cloud to conceal gaps that appear when zooming into the point cloud. The dynamically backfilling fills a gap with dynamically generated points that continue a texture, contour, pattern, shape, coloring, and/or other commonality of an original set of points from the point cloud that form a single continuous surface with that gap. The system defines a model based on images of an object or scene. The model represents the object or scene at different zoom depths with different dynamically generated points. The system determines that a requested render position exposes a gap in the original set of points. The system fills the gap by using the model to generate points at positions over the gap that continue a shape, form, or structure of a single continuous surface formed by the original set of points.