Moving-Object Group Matching for Automatic Camera Calibration

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Solution Overview

Problem

Existing camera calibration systems require manual input of road lanes and a measuring vehicle, which is time-consuming and labor-intensive.

Innovation Solution

An information processing apparatus that determines whether moving object groups captured by multiple cameras are the same, using machine-learning models to estimate the installation relationship between cameras based on the movement modes of these groups.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual input of road lanes and measuring vehicle are used for camera calibration, then calibration can be performed, but the process becomes time-consuming and labor-intensive

Engineering Contradiction:
Improvecamera calibration accuracyVSAvoidcalibration time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The system automatically identifies moving objects in images from multiple cameras and performs calibration without requiring manual input of road lanes or deployment of measuring vehicles. The calibration process serves itself by using naturally occurring traffic data rather than requiring external measurement equipment or human operators.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical system of manual road lane input and measuring vehicle deployment with an automated image processing system that identifies moving objects and calculates camera parameters through computational algorithms.

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

2Measurement precision

If manual input of road lanes is used for camera calibration, then calibration can be performed, but manual labor is required

Engineering Contradiction:
Improvecamera calibration accuracyVSAvoidoperation simplicity
Core Design Contradiction:
Measurement precisionVSEase of operation

Solution Approach 1:

The calibration system automatically processes images and identifies moving objects without requiring operators to manually input road lane information. The system performs self-calibration using algorithms that detect and track moving objects across multiple camera views.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The patent replaces manual operations of road lane input with automated image processing and moving object recognition algorithms that perform calibration calculations based on detected object positions and movements.

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

3Measurement precision

If measuring vehicle and worker are used for calibration, then calibration can be performed, but multiple components and labor are required

Engineering Contradiction:
Improvecamera calibration accuracyVSAvoidcalibration system complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent extracts the essential calibration function from complex measurement vehicles and reduces it to an automated image processing system that uses moving objects already present in the traffic environment, eliminating the need for specialized measurement equipment.

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The system uses ordinary traffic moving objects for multiple purposes: they serve as both the subject of traffic monitoring and as reference objects for camera calibration, eliminating the need for separate calibration equipment and reducing system complexity.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentEP4579626A1Information processing device, information processing method, and information processing program
Publication Date: 2025.07.02 KYOCERA CORP
  • EP4579626A1 patent drawingFigure 1
  • EP4579626A1 patent drawingFigure 2
  • EP4579626A1 patent drawingFigure 3~4

AI summary

An information processing apparatus (200) includes a determiner (242) configured to determine whether a first moving object group identified from a first image captured by a first camera and a second moving object group identified from a second image captured by a second camera are an identical moving object group, and an outputter (243) configured to output installation relationship information identifying an installation relationship between the first camera and the second camera based on a movement mode of the first moving object group and a movement mode of the second moving object group determined to be the identical moving object group.