3D Feature Descriptors With Camera Pose Indexing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Machine vision techniques, such as SLAM and AR, face challenges in accurately identifying objects across different observation directions and distances due to variations in 2D feature descriptors, which affect comparison processes.
Innovation Solution
The implementation of an electronic device equipped with multiple imaging cameras and a depth sensor, utilizing a processing architecture that generates and utilizes 3D feature descriptors by indexing 2D feature descriptors with camera pose information, enabling efficient identification and comparison of spatial features across varying camera poses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If 2D feature descriptors are used for object identification, then the system can operate without external positioning information, but the accuracy of object identification deteriorates when comparing descriptors from different observation directions and distances
Solution Approach 1:
The patent transforms 2D feature descriptors into 3D feature descriptors by incorporating depth information from the depth sensor. This dimensional enhancement allows the system to maintain identification accuracy across different observation directions and distances, as the 3D descriptors capture the geometric structure of objects in three-dimensional space rather than being limited to two-dimensional image plane representations.
Solution Approach 2:
The patent changes the parameter representation by indexing feature descriptors with camera pose information (position and orientation). This allows the system to normalize and compare features from different viewpoints by transforming them into a common reference frame, thereby maintaining identification accuracy regardless of observation direction or distance variations.
2Measurement precision
If multiple imaging cameras and depth sensor are used to generate 3D feature descriptors, then object identification accuracy improves, but device complexity increases
Solution Approach 1:
The patent merges the functionality of multiple imaging cameras and a depth sensor into a unified processing architecture that generates 3D feature descriptors. By combining these sensors and processing their data together, the system achieves accurate object identification while managing complexity through integrated processing rather than separate independent systems.
Solution Approach 2:
The patent creates 3D feature descriptors as digital representations (copies) of physical object features captured by multiple sensors. These descriptor copies can be stored, processed, and compared without requiring the physical sensors to be actively engaged, reducing operational complexity while maintaining identification accuracy.
3Measurement precision
If 3D feature descriptors with camera pose information are used, then feature comparison accuracy improves across different views, but processing complexity increases
Solution Approach 1:
The patent performs preliminary processing by pre-computing and storing 3D feature descriptors with indexed camera pose information during the mapping phase. This preliminary action allows subsequent comparisons to be performed more efficiently, as the heavy lifting of 3D reconstruction and pose estimation has already been completed, reducing real-time processing complexity.
Data Source
AI summary
A method includes determining a first two-dimensional (2D) feature descriptor from a first image captured by an imaging camera in a first pose at a time of capture of the first image, the first pose including a first observation direction of the imaging camera. The method further includes storing, at an electronic device, a 3D feature descriptor including the first 2D feature descriptor and a representation of the first pose of the imaging camera. The method additionally includes determining a second 2D feature descriptor from a second image captured by the imaging camera in a second pose at a time of capture of the second image, the second pose including a second observation direction of the imaging camera. The method also includes storing the 3D feature descriptor with the second 2D feature descriptor and a representation of the second pose of the imaging camera.