An event camera calibration method based on wavelet transform
CN118608621BActive Publication Date: 2026-05-26ANHUI UNIV
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ANHUI UNIV
- Filing Date
- 2024-06-07
- Publication Date
- 2026-05-26
AI Technical Summary
Technical Problem
Existing event camera calibration methods are insufficient in terms of flexibility and accuracy, making it difficult to meet the high efficiency and reliability requirements of computer vision applications.
Method used
A wavelet transform-based method is adopted to display a striped pattern on an LCD screen by triggering an event camera. Gaussian filtering is used to eliminate noise, wavelet transform is combined to extract feature points, and linear and nonlinear optimization algorithms are combined to calculate camera parameters to achieve accurate calibration.
Benefits of technology
It improves the accuracy and flexibility of event camera calibration, reduces the impact of noise, and achieves efficient and accurate feature point extraction and parameter calculation.
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Figure CN118608621B_ABST
Abstract
This invention discloses an event camera calibration method based on wavelet transform, which can quickly extract feature points and improve calibration accuracy and speed. The target, displayed as a striped pattern on an LCD screen, serves as the two-dimensional calibration target, showing both horizontal and vertical stripe images. The screen flashes at a certain frequency to trigger events. During calibration, the event camera acquires and captures horizontal and vertical stripe event stream data. An appropriate time window is selected, and the event stream is accumulated into two-dimensional event frames, which are then converted into image information. Wavelet transform is then used to calculate the wrap-around phase map in both directions. The feature points are located at the 2π phase value between the horizontal and vertical wrap-around phases, thus obtaining the pixel coordinates of the feature points. This invention uses image transformation technology to extract the phase map, eliminating reliance on image intensity for feature point detection and achieving accurate feature point extraction.
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