Camera Reliability Selection for Visual SLAM
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Solution Overview
Problem
In a limited computational resource environment, it is challenging to effectively utilize multiple cameras for self-location estimation using visual simultaneous localization and mapping (SLAM) techniques, as existing methods struggle to accurately select the most reliable camera for precise location estimation.
Innovation Solution
A location estimation apparatus that includes a reliability calculation circuit, a selection circuit, and a self-location estimation circuit, which calculates the reliability of each camera based on factors like feature point distribution, object detection, moving direction, and past location information to select the most suitable camera for self-location estimation using techniques like SLAM and structure from motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple cameras are used for self-location estimation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments the camera selection process into distinct functional modules: a reliability calculation unit that evaluates multiple cameras independently, and a selection unit that chooses the optimal camera based on calculated reliability metrics. This segmentation allows each camera to be assessed separately without requiring complex inter-camera coordination, thereby improving location estimation accuracy while managing system complexity through modular design.
2Measurement precision
If all cameras are used in limited computational resource environment, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The system extracts only the most reliable camera from the set of available cameras based on calculated reliability metrics. Instead of processing data from all cameras simultaneously, the selection unit identifies and extracts the single best camera for current conditions, significantly reducing computational resource requirements while maintaining high location estimation accuracy. This extraction approach eliminates redundant processing of lower-quality camera data.
3Measurement precision
If camera reliability is calculated based on multiple factors, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The reliability calculation unit serves multiple functions simultaneously: it evaluates feature point distribution quality, assesses object detection performance, analyzes moving direction consistency, and integrates past location information. By consolidating these diverse evaluation criteria into a single multi-functional reliability metric for each camera, the system achieves comprehensive camera assessment without requiring separate complex mechanisms for each evaluation aspect.
Data Source
AI summary
A location estimation apparatus includes a reliability calculation circuit, a selection circuit, and a self-location estimation circuit. The reliability calculation circuit calculates a reliability with respect to location estimation for a plurality of devices capturing a plurality of input images. The selection circuit selects one of the devices based on the reliability. The self-location estimation circuit performs self-location estimation based on the image captured by the selected device.