Camera Network Calibration via Video Time Signatures

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Solution Overview

Problem

Large-scale urban surveillance camera networks often lack accurate calibration and synchronization of camera positions and orientations, making it a tedious and expensive task to determine the exact global location and orientation of each camera, which is crucial for effective video matching and traffic monitoring.

Innovation Solution

A method for automatically matching video streams from multiple cameras by calculating time signatures and temporal offsets, allowing for the identification of moving objects across different camera views and determining spatial relationships between fields of view, thereby enabling accurate tracking and synchronization without the need for extensive calibration.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If standard calibration process is performed for each camera, then measurement precision of camera position and orientation is improved, but device complexity and time consumption increase significantly

Engineering Contradiction:

Improvecamera position and orientation accuracyVSAvoidcalibration process complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system performs self-calibration by automatically computing camera positions and orientations through video stream correlation and temporal offset calculation, eliminating the need for manual calibration operations. The cameras themselves provide the data needed for their own positioning through the movement patterns of objects they capture.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Moving objects serve as intermediaries to establish spatial relationships between cameras. By tracking how the same moving object appears across multiple camera views with different temporal offsets, the system infers camera positions and orientations without direct measurement equipment.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If standard calibration process is performed for each camera, then measurement precision of camera position and orientation is improved, but loss of time increases

Engineering Contradiction:

Improvecamera position and orientation accuracyVSAvoidcalibration time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs calibration actions continuously in the background using ongoing video streams, rather than requiring a separate preliminary calibration phase. The calibration data is accumulated and refined over time as cameras continuously capture and process video data of moving objects.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The calibration process operates continuously using the ongoing video monitoring function, converting the continuous stream of video data into calibration information. The same video streams used for monitoring also serve for calibration, eliminating idle calibration phases.

Inventive Principle:

Principle #20Continuity of useful action

3Measurement precision

If standard calibration process is performed for each camera, then measurement precision of camera position and orientation is improved, but productivity decreases

Engineering Contradiction:

Improvecamera position and orientation accuracyVSAvoiddeployment efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system enables rapid deployment by allowing cameras to self-calibrate automatically upon installation, eliminating the need for technician intervention for each camera. This self-service capability dramatically increases deployment productivity while maintaining measurement precision.

Inventive Principle:

Principle #25Self-service

4Measurement precision

If temporal offset calculation is applied to video streams, then correspondence between video streams is improved, but device complexity increases

Engineering Contradiction:

Improvevideo stream correspondence accuracyVSAvoidvideo processing complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system replaces complex mechanical calibration equipment with computational methods. By using algorithms to calculate temporal offsets from video data patterns, the system achieves precise video stream correspondence through software rather than hardware complexity.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS9942450B2Automatic time signature-based video matching for a camera network

Publication Date: 2018.04.10 AGT INTERNATIONAL INC

AI summary

A method for automatically matching video streams from two cameras of a camera network includes obtaining a video stream of frames that are acquired by each of the cameras. Each video stream includes images of moving objects. A time signature for each of the video streams is calculated. Each time signature is indicative of a time at which an image of one the objects is located at a predetermined part of the frame. A temporal offset of one of the signatures relative to the other signature is calculated such that, when applied to one of the signatures, a correspondence between the signatures is maximized. The temporal offset is applicable to video streams that are acquired by the two cameras to determine if a moving object that is imaged by one of the cameras is identical to a moving object that is imaged by the other camera.