Onboard Camera Data Extraction and Classification System

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Solution Overview

Problem

Existing information providing systems that utilize onboard camera image data are limited in their ability to cater to diverse user needs, primarily focusing on traffic congestion information, and lack flexibility in extracting and classifying feature information relevant to specific user requests regarding people and vehicles.

Innovation Solution

An information providing system that collects, extracts, and classifies feature information from onboard camera data based on user-defined location, extraction items, and classification items, including movement information, age, sex of individuals, and vehicle type, while preventing duplicate data extraction and estimating information during non-capture periods, with the capability to acquire new data when needed.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If the system extracts and classifies feature information from onboard camera data based on user requests, then the versatility and adaptability of the system is improved, but the device complexity increases due to multiple extraction and classification units

Engineering Contradiction:

Improveability to provide diverse information based on user needsVSAvoidsystem structure with multiple units for extraction and classification

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The information providing system is designed with extraction units and classification units that can handle multiple types of feature information (movement information, age, sex, vehicle type, etc.) through a unified architecture. The system can extract various features from onboard camera data and classify them according to different classification items, making the system versatile for different user needs without requiring separate dedicated systems for each function.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system divides the information processing function into distinct modules: extraction units that extract specific feature information from image data, and classification units that classify the extracted information by classification items. This segmentation allows each unit to specialize in specific tasks while working together through a coordinated framework, managing complexity through functional decomposition.

Inventive Principle:

Principle #1Segmentation

2Quantity of substance

If the system collects and processes image data from multiple onboard cameras, then the quantity and quality of information is improved, but the loss of time increases due to data collection and processing requirements

Engineering Contradiction:

Improveamount of feature information extractedVSAvoidtime required for data collection and processing

Core Design Contradiction:

Quantity of substanceVSLoss of time

Solution Approach 1:

The system performs preliminary extraction of feature information from image data captured by multiple onboard cameras, storing the extracted features (movement information, age, sex, vehicle type, etc.) in advance. When users request information, the pre-extracted data can be quickly retrieved and classified without requiring real-time processing of raw image data, significantly reducing the time loss for information delivery.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously collects and processes image data from multiple onboard cameras, maintaining an ongoing stream of extracted feature information. This continuous processing ensures that information is always available and up-to-date, allowing the system to quickly respond to user requests without interruption or delay caused by batch processing.

Inventive Principle:

Principle #20Continuity of useful action

3Measurement precision

If the system provides detailed feature information extraction and classification, then the measurement precision of information is improved, but the difficulty of detecting and measuring increases due to the complexity of extracting multiple feature types

Engineering Contradiction:

Improveaccuracy of extracted feature informationVSAvoidcomplexity of extracting and classifying multiple feature types

Core Design Contradiction:

Measurement precisionVSDifficulty of detecting and measuring

Solution Approach 1:

The system employs specialized extraction units that are optimized for detecting specific feature types (movement information, age, sex, vehicle type, etc.). Each extraction unit focuses on its specific feature type with dedicated algorithms and processing methods, ensuring high measurement precision for each feature while managing the overall complexity through specialization rather than attempting to handle all features with a single generic processor.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11718176B2Information providing system, information providing method, information terminal, and information display method

Publication Date: 2023.08.08 TOYOTA JIDOSHA KK

AI summary

An onboard camera image application system includes multiple vehicles, an information providing system, and a PC. In the information providing system, a collection server collects image data captured by onboard cameras of the vehicles. An analysis server extracts, from the image data captured around one location, feature information associated with an extraction item for a person or a vehicle around the location. The analysis server also classifies the extracted feature information by classification item. A providing server sends the classified feature information to the PC of a user. The user is able to set a location to be processed, through the PC, and is also able to set the extraction item or the classification item.