Spatial Synchronization of Multiple Cameras Using Lighting Signals
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Solution Overview
Problem
Conventional methods for spatial synchronization of multiple cameras are labor-intensive, inaccurate, and inefficient, often requiring manual setup and the use of measurement targets like checkerboard patterned-boards and identifiable markers.
Innovation Solution
An electronic device that uses a lighting device with a grid of lights and an edge light to emit synchronization signals, allowing for automatic calibration of cameras by determining extrinsic parameters through pattern recognition and simultaneous localization and mapping (SLAM) processes, eliminating the need for manual setup and measurement targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods use manual setup with measurement targets like checkerboard patterned-boards and identifiable markers for spatial synchronization, then the calibration can be performed, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent removes measurement targets (checkerboard patterns and markers) from the calibration scene entirely. Instead of using external targets, the system extracts calibration information directly from the scene content captured by cameras, eliminating the need for manual placement of measurement artifacts and significantly reducing setup time while maintaining calibration accuracy
Solution Approach 2:
The system performs self-calibration by using the cameras themselves to capture and process calibration information. The cameras capture images of the scene, and the system automatically extracts extrinsic parameters from the captured images through image processing and matching algorithms, eliminating the need for manual operator intervention in the calibration process
2Measurement precision
If conventional methods use manual execution for spatial synchronization setup, then the calibration can be performed, but the process becomes difficult to implement and less efficient
Solution Approach 1:
The patent replaces manual mechanical operations (physically setting up measurement targets, manually adjusting camera positions) with automated computational processes. The system uses image processing algorithms, feature matching, and optimization techniques to automatically determine camera extrinsic parameters from captured images, significantly improving calibration efficiency and ease of implementation
Solution Approach 2:
The patent introduces captured images as an intermediary between the cameras and the calibration process. Instead of directly manipulating physical measurement targets, the system captures images of the scene and processes these images computationally to extract calibration information, creating an automated pipeline that improves both efficiency and reproducibility
3Measurement precision
If conventional methods use measurement targets for spatial synchronization, then the calibration can be performed, but the process requires additional equipment and setup complexity
Solution Approach 1:
The patent extracts calibration capability from external measurement targets and embeds it within the scene itself. By removing checkerboard patterns and markers, the system reduces the number of components needed for calibration, simplifying the overall setup while maintaining the ability to accurately determine camera extrinsic parameters through scene-based feature extraction
Data Source
AI summary
An electronic device is provided that determines initial three-dimensional (3D) coordinates of a lighting device. The electronic device controls an emission of light from the lighting device based on control signals. The emitted light includes at least one of a pattern of alternating light pulses or a continuous light pulse. The electronic device controls a plurality of imaging devices to capture a first plurality of images that include information about the emitted light. Based on the determined initial 3D coordinates and the information about the emitted light included in the first plurality of images, the electronic device estimates a plurality of rotation values and a plurality of translation values of each imaging device. Based on the plurality of rotation values and the plurality of translation values, the electronic device applies a simultaneous localization and mapping process for each imaging device, for spatial synchronization of the plurality of imaging devices.