Unified DVS and Camera Calibration via LED Grid Board
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Solution Overview
Problem
Current technologies are unable to effectively calibrate Dynamic Vision Sensors (DVS) with conventional cameras due to their different characteristics, which hinders integrated applications and data fusion.
Innovation Solution
A unified calibration method and system that uses a calibration board with high-frequency LEDs and grids, allowing DVS and cameras to detect intensity changes and calculate an extrinsic matrix by integrating pixel data from consecutive frames, enabling coordinate system transformations and alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional camera calibration methods are used for DVS, then the calibration process can be simplified, but the calibration accuracy deteriorates due to different sensor characteristics
Solution Approach 1:
The calibration process is segmented into distinct phases: camera calibration using traditional methods, DVS calibration using event-based methods, and fusion calibration combining both. This segmentation allows each sensor type to be calibrated with its optimal method while maintaining overall system integration.
Solution Approach 2:
A calibration board with high-contrast patterns serves as an intermediary object that both camera and DVS can detect. The board provides common reference features that enable accurate extrinsic parameter calculation between the two different sensor types without requiring direct comparison of their different data formats.
2Adaptability or versatility
If DVS and camera are bound for integrated applications, then the versatility of the system is improved, but the difficulty of detecting and measuring increases due to different data characteristics
Solution Approach 1:
The system transforms DVS event data into frame-based representations with adjustable temporal integration windows. By changing the integration parameter, the system can optimize between temporal resolution (smaller windows) and signal-to-noise ratio (larger windows), making the data more compatible with traditional camera processing pipelines.
Solution Approach 2:
The calibration establishes a 6-degree-of-freedom spatial transformation matrix that maps coordinates from DVS event space to camera image space. This dimensional transformation enables features detected by DVS (asynchronous events) to be accurately projected onto the camera's 2D image plane, facilitating integrated applications.
3Measurement precision
If high-frequency LEDs are used on calibration board, then the DVS detection capability is improved, but the camera image quality may deteriorate due to light saturation
Solution Approach 1:
The high-frequency LEDs on the calibration board are driven with periodic pulsing at frequencies optimized for DVS detection. This periodic illumination creates strong intensity transitions that DVS excels at detecting, while the duty cycle is controlled to prevent camera saturation during integration periods.
Solution Approach 2:
The system dynamically adjusts LED brightness and pulsing frequency based on detection requirements. During DVS calibration phases, higher intensity and frequency are used to maximize event generation. During camera capture phases, intensity is reduced to prevent saturation, demonstrating dynamic adaptation to different operational modes.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and stable calibration between DVS and cameras, facilitating integrated applications and data fusion, improving the accuracy and versatility of vision sensor systems.
Implementation Method 1
setting up a calibration board comprising calibration grids and a plurality of high-frequency LEDs (Light-Emitting Diodes)
Implementation Method 2
The DVS (Dynamic Vision Sensor) only captures intensity changes and then creates asynchronous pixels
Data Source
AI summary
A unified calibration method between a DVS and a camera, in which a special calibration board is set up which consists of a calibration grid pattern and LEDs attached to the corners of the calibration grids. The camera finds the corners of calibration grid by capturing the image, and the DVS finds the same corners by detecting the intensity changes of the LEDs at the corners, to establish a unified world coordinate system as a reference coordinate system. After performing the calibration and coordinate system transformations, an extrinsic matrix between the DVS and the camera can be obtained.