N-Dimensional Object Representation Using Enriched Voxel Tensors
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Solution Overview
Problem
Existing data formats often focus on a single dimension, such as visual data, temporal information, or thermal imaging, failing to integrate multiple dimensions required for comprehensive understanding in real-world applications like autonomous vehicle navigation.
Innovation Solution
A data structure called daxle is developed, encapsulating high-resolution images, accurate timestamps, thermal imaging layers, and 6 DOF tracking information within a unified package, using enriched BOMs and neural networks to generate 2D pixels for a tensor, enabling a holistic representation of environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing data formats focus on a single dimension (visual, temporal, or thermal), then the data structure remains simple and manageable, but the ability to comprehend complex real-world scenarios is insufficient
Solution Approach 1:
The patent merges multiple single-dimension data formats (visual images, temporal timestamps, thermal imaging, 6DOF tracking) into a unified multi-dimensional data structure called daxle. This combining approach enables the system to comprehend complex real-world scenarios by integrating diverse data types while managing them through a single cohesive structure rather than separate formats.
Solution Approach 2:
The daxle data structure serves multiple functions simultaneously: it stores visual data, temporal information, thermal imaging, and spatial tracking data within a single universal format. This multi-functional design allows the same data structure to handle various types of sensor data from autonomous vehicles, eliminating the need for separate specialized formats for each data type.
2Loss of information
If multiple data dimensions are integrated into a unified format, then comprehensive scenario understanding is achieved, but the data processing complexity increases
Solution Approach 1:
The patent segments the complex multi-dimensional data into distinct functional components within the daxle structure: visual data layer, temporal data layer, thermal imaging layer, and 6DOF tracking layer. Each component maintains its specific characteristics while being organized within a unified framework, making the integrated data manageable and processable without losing information from any dimension.
Data Source
AI summary
Generating data enriched voxels is provided. The method comprises receiving image data of a three-dimensional (3D) object. A number of key vertices are detected within the 3D object, and a bill of materials (BOM) is created for each key vertex. The BOM for each key vertex is then enriched with production data and sensor data, wherein the enriched BOM for each key vertex describes environmental conditions within a defined area around the 3D object. The enriched BOM for each key vertex are then fed into a respective neural network that generates a two-dimensional (2D) pixel containing all data from the enriched BOM, wherein the 2D pixel forms part of a tensor of 2D pixels.