Mesh Vector Indexing for Depth Data Processing
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Solution Overview
Problem
The use of unprocessed depth information from depth images leads to complex calculations and large data processing, resulting in degraded calculation efficiency in various applications such as obstacle detection and AR/VR, due to unnecessary information being included in the data.
Innovation Solution
An image processing apparatus that divides images into a mesh shape of polygons, acquires and transforms depth information into three-dimensional space coordinates, calculates element vectors, and generates a vector list with unique indexes to reduce data storage and improve calculation efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If unprocessed depth information is used directly for calculation, then complete information is available, but calculation becomes complicated and data processing volume increases
Solution Approach 1:
The patent segments the depth image into a mesh structure of polygons, where each polygon is defined by vertex coordinates. This segmentation transforms the continuous depth information into discrete geometric elements (vertices and polygons), reducing the data structure complexity while preserving the essential spatial relationships needed for calculations.
Solution Approach 2:
The patent extracts only the necessary geometric information (vertex coordinates and polygon structures) from the complete depth image data. By taking out only the essential elements needed for spatial calculations, it eliminates redundant information while maintaining calculation accuracy, thus improving processing efficiency.
2Loss of information
If unprocessed depth information is used directly, then all original data is retained, but a very large amount of data has to be processed
Solution Approach 1:
The depth image is divided into a mesh of polygons with defined vertices. This segmentation reduces the data representation from continuous pixel-based depth values to discrete polygon vertices, significantly reducing the quantity of data that needs to be processed while retaining the essential geometric information.
Solution Approach 2:
The patent changes the parameter representation from pixel-based depth values to geometric parameters (vertex coordinates and polygon structures). This parameter transformation reduces the data volume by representing complex depth information through simplified geometric primitives that require fewer parameters to describe.
3Productivity
If depth information is converted into geometry information, then calculation efficiency improves, but data transformation complexity increases
Solution Approach 1:
The patent performs preliminary conversion of depth information into geometric mesh structures before actual calculations are needed. By pre-processing the depth data into vertex coordinates and polygon definitions, it prepares the data in an optimized format that enables efficient subsequent calculations, avoiding the need for complex transformations during runtime.
Data Source
AI summary
A unit that divides an image into a mesh shape and acquires depth information and an X-coordinate and a Y-coordinate for vertices of each grid, a unit that transforms vertex data into three-dimensional space coordinates expressed by a predetermined coordinate system, a unit that calculates line segment vectors and a normal vector that constitute each grid based on the three-dimensional space coordinates of each vertex, a vector management part that assigns indexes for distinguishing unique vectors from each other to the respective unique vectors, and generates a vector list in which the unique vectors and the indexes are respectively associated with each other, and a unit that stores therein indexes of the vectors that constitute each grid, while being associated with the grid.