Dynamic Calibration Object for DVS Camera Parameter Determination
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Solution Overview
Problem
Dynamic vision sensors (DVS) cameras, which sense only changes, face challenges in camera calibration due to their inability to capture still images, making traditional calibration methods ineffective, and require novel solutions to determine camera calibration parameters accurately.
Innovation Solution
A method and device that utilize a moving calibration object, such as a ball equipped with sensors and communication units, to read in both imaging and reference trajectories synchronously, allowing for the calculation of compensation parameters by detecting accelerations and position changes, enabling accurate calibration of DVS cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration methods using static grids are used, then calibration parameters can be obtained, but these methods are ineffective for dynamic vision sensors that sense only changes
Solution Approach 1:
The patent transforms the calibration approach from static to dynamic by using a moving calibration object whose trajectory is recorded over time. The calibration object moves through the camera's field of view, creating dynamic image sequences that DVS cameras can detect. This dynamic calibration process generates trajectory data that can be used to calculate intrinsic and extrinsic parameters suitable for change-detecting sensors.
Solution Approach 2:
The patent replaces the traditional optical-mechanical grid system with a motion-based trajectory system. Instead of using physical grids that require complex mechanical positioning, the solution uses a moving calibration object with its position tracked over time, substituting static mechanical structures with dynamic motion patterns that DVS cameras can naturally capture.
2Adaptability or versatility
If a moving calibration object is used to enable DVS calibration, then adaptability to DVS cameras is achieved, but the calibration process becomes more complex
Solution Approach 1:
The calibration object serves multiple functions: it acts as a physical marker for tracking, provides known trajectory information for parameter calculation, and generates sufficient dynamic data for both intrinsic and extrinsic parameter determination. This multi-functional design simplifies the overall system by using a single object to accomplish what would otherwise require multiple separate calibration components.
Solution Approach 2:
The calibration object is designed to be self-contained, carrying its own identification features and movement information. It autonomously provides the necessary calibration data through its motion, eliminating the need for external tracking infrastructure or complex positioning systems. The object itself generates the calibration information needed.
3Productivity
If synchronized detection in image coordinates and world coordinates is performed, then data volume is reduced and calibration parameter ascertainment is accelerated, but precise coordination between detection systems is required
Solution Approach 1:
The system uses feedback from the calibration object's known trajectory to synchronize and coordinate the image coordinate detection with world coordinate detection. The object's pre-defined or pre-measured path serves as a reference that both detection systems must align with, providing a feedback mechanism that ensures temporal and spatial coordination between the camera and external detection device.
Data Source
AI summary
A method for calibrating a camera. The method includes a step of reading in and a step of ascertaining, an imaging trajectory and a reference trajectory of a moving calibration object detected by using the camera being read in in the step of reading in, the imaging trajectory representing a trajectory imaged in image coordinates of the camera and the reference trajectory representing the trajectory in world coordinates, and at least one calibration parameter for the camera being ascertained in the step of ascertaining by using the imaging trajectory and the reference trajectory.