Geometry Image Pose Detection for 3D Objects
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Solution Overview
Problem
Detecting the pose of 3D objects with high accuracy and speed from captured sensor data, particularly on resource-constrained devices like smartphones and augmented reality headsets, is challenging due to the complexity of 3D shapes and the need for real-time processing.
Innovation Solution
The use of geometry images as a 2D parameterized representation of 3D shapes allows for efficient pose detection by reducing the number of branches and loops in the computation process, enabling parallelization with hardware accelerators and facilitating real-time pose estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional 3D pose detection methods are used, then measurement precision is improved, but device complexity increases and processing speed decreases
Solution Approach 1:
The patent creates a simplified 2D copy (geometry image) of the 3D object surface, which can be efficiently processed while still enabling accurate pose detection. The geometry image is a parameterized representation that maps 3D surface geometry to a 2D domain, allowing fast comparison with captured images without requiring complex 3D processing.
Solution Approach 2:
The patent transforms the 3D pose detection problem into a 2D image matching problem by using geometry images. This dimensionality reduction from 3D to 2D simplifies the computational complexity while maintaining the essential geometric information needed for accurate pose estimation.
2Measurement precision
If traditional 3D pose detection methods are used, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent creates a simplified 2D copy (geometry image) of the 3D object surface, which can be efficiently processed while still enabling accurate pose detection. The geometry image is a parameterized representation that maps 3D surface geometry to a 2D domain, allowing fast comparison with captured images without requiring complex 3D processing.
Solution Approach 2:
The patent transforms the 3D pose detection problem into a 2D image matching problem by using geometry images. This dimensionality reduction from 3D to 2D simplifies the computational complexity while maintaining the essential geometric information needed for accurate pose estimation.
3Productivity
If real-time pose detection is implemented on resource-constrained devices, then productivity is improved, but measurement precision deteriorates
Solution Approach 1:
The patent creates a simplified 2D copy (geometry image) of the 3D object surface, which can be efficiently processed while still enabling accurate pose detection. The geometry image is a parameterized representation that maps 3D surface geometry to a 2D domain, allowing fast comparison with captured images without requiring complex 3D processing.
Solution Approach 2:
The patent changes the representation parameters from full 3D geometry to a 2D parameterized geometry image. This parameter transformation enables real-time processing on resource-constrained devices while preserving sufficient geometric detail for accurate pose detection through optimization-based fitting.
Data Source
AI summary
There is an apparatus for detecting pose of an object. The apparatus comprises a processor configured to receive captured sensor data depicting the object. It also has a memory storing a parameterized model of a class of 3D shape of which the object is a member, where an instance of the model is given as a mapping from a point in a 2D rectangular grid to a 3D position. The processor is configured to compute values of the parameters of the model by calculating an optimization to fit the model to the captured sensor data, using the parametrized mapping. The processor is configured to output the computed values of the parameters comprising at least global position and global orientation of the object.