Thermal Video Quantization Parameter Management

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Solution Overview

Problem

Conventional thermal video systems face challenges in accurately processing thermal video data due to its wide dynamic range, leading to false event detection caused by changes in temperature and contrast, as analytics algorithms are not aware of the quantization parameters used by thermal cameras.

Innovation Solution

The method involves determining quantization parameters for thermal video data, including constructing histograms and calculating thresholds, to generate quantized video data and accompanying information, which is then transmitted to a video analytics server, allowing for re-quantization of previously processed data when parameters change, ensuring consistent video analytics.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If thermal video data is quantized using conventional methods, then the video data can be processed and transmitted, but false event detection occurs due to changes in temperature and contrast

Engineering Contradiction:

Improveevent detection accuracyVSAvoidquantization parameter management

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system performs preliminary quantization at the camera before transmission, and maintains a history of quantization parameters. When parameters change, the system proactively re-quantizes previously captured video data to maintain consistency, preventing false event detection before it occurs.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback by monitoring quantization parameter changes and using this information to trigger re-quantization of historical video data. The analytics server receives quantization parameter information and uses it to determine when re-quantization is necessary to maintain detection accuracy.

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If quantization parameters change due to temperature and contrast variations, then the video adapts to different conditions, but analytics algorithms produce false positives because they are unaware of parameter changes

Engineering Contradiction:

Improvevideo adaptation to temperature changesVSAvoidanalytics accuracy

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system introduces quantization parameter information as an intermediary between the video capture process and the analytics algorithms. This metadata allows analytics algorithms to understand when re-quantization has occurred, preventing false positives while maintaining adaptability to changing thermal conditions.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system explicitly tracks and communicates quantization parameter changes to the analytics server. When parameters change, the system re-quantizes video data and notifies the analytics server, allowing algorithms to adjust their operation based on the new parameter state rather than producing false alarms.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If re-quantization is performed when parameters change, then analytics accuracy is maintained, but additional processing time and computational resources are required

Engineering Contradiction:

Improvevideo analytics consistencyVSAvoidprocessing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs re-quantization selectively rather than continuously. It monitors quantization parameter changes and only triggers re-quantization when parameters actually change, performing the minimum necessary processing to maintain analytics consistency without wasting resources on unnecessary re-quantization operations.

Inventive Principle:

Principle #16Partial or excessive action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach improves the accuracy of motion detection and object identification in thermal video by maintaining consistent video analytics despite changes in scene temperature and dynamic range, reducing false alarms and enhancing video quality for both processing and display purposes.

Implementation Method 1

thermal imaging cameras that are configured to detect radiation in the infrared range of the electromagnetic spectrum

Methodology Applied

Scientific EffectInfrared radiation detection: Infrared Radiation

Data Source

PatentUS8934020B2Integrated video quantization

Publication Date: 2015.01.13 PELCO INC

AI summary

Techniques for processing video content in a video camera are provided. The techniques include a method for processing video content in at video camera according to the disclosure includes capturing thermal video data using a thermal imaging sensor, determining quantization parameters for the thermal video data, quantizing the thermal video data to generate quantized thermal video data content and video quantization information, and transmitting the quantized thermal video data stream and the video quantization information to a video analytics server over a network.