Wide-Angle and PTZ Camera Calibration Using 3D Point Pairs

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Solution Overview

Problem

Existing surveillance systems face challenges in efficiently and accurately calibrating wide-angle and pan-tilt-zoom cameras for effective monitoring and capturing detailed information about targets within a wide area, requiring manual intervention and lacking automation.

Innovation Solution

A method and system for automatic camera calibration between wide-angle and PTZ cameras using 3D information from overlapping fields of view, employing algorithms like Levenberg-Marquardt to determine rotation matrices based on point pairs in captured images, reducing human effort and improving accuracy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual calibration is used between wide-angle and PTZ cameras, then calibration accuracy can be achieved, but the calibration process is time-consuming and requires human intervention

Engineering Contradiction:
Improvecalibration accuracyVSAvoidcalibration time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The system performs automatic calibration by having the PTZ camera autonomously capture images of calibration objects detected in the wide-angle camera's field of view. The processor automatically identifies corresponding points between images and computes the rotation matrix without human intervention, enabling the system to calibrate itself

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The wide-angle camera first captures an image to identify calibration objects and their coordinates before the PTZ camera performs detailed imaging. This preliminary detection phase prepares the calibration process by pre-identifying target objects and their positions, streamlining the subsequent automated calibration steps

Inventive Principle:
Principle #10Preliminary action

2Productivity

If automatic calibration algorithms are implemented, then calibration efficiency is improved, but system complexity increases

Engineering Contradiction:
Improvecalibration efficiencyVSAvoidsystem complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent replaces manual mechanical calibration operations with automated image processing and computational algorithms. The processor uses computer vision techniques to detect calibration objects, extract feature points, and calculate the rotation matrix automatically, substituting human-operated mechanical adjustment with intelligent software-based calibration

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If multiple image sets are processed for calibration, then calibration precision is enhanced, but processing complexity increases

Engineering Contradiction:
Improvecalibration precisionVSAvoidprocessing complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The calibration process is divided into distinct segments: the wide-angle camera performs preliminary detection to identify calibration objects and their coordinates, then the PTZ camera captures detailed images of these objects. The processor separately handles coordinate extraction from wide-angle images and precise measurement from PTZ images, then integrates results to compute the rotation matrix. This segmentation allows multiple image sets to be processed systematically while managing complexity through structured workflow division

Inventive Principle:
Principle #1Segmentation

Data Source

PatentEP3884468B1Methods and systems for camera calibration
Publication Date: 2026.01.28 ZHEJIANG DAHUA TECH CO LTD
  • EP3884468B1 patent drawingFigure 1
  • EP3884468B1 patent drawingFigure 2
  • EP3884468B1 patent drawingFigure 3

AI summary

An image capture method may include obtaining two or more sets of images. The two or more sets of images may include a first image captured by a first image capture device and a second image captured by a second image capture device. The method may also include determining, for a set of images, two or more pairs of points. Each of the two or more pairs of points may include a first point in the first image and a second point in the second image, and the first point and the second point may correspond to a same object. The method may also include determining a first rotation matrix based on the pairs of points in the two or more sets of images. The first rotation matrix may be associated with a relationship between positions of the first image capture device and the second image capture device.