Vehicle Interior Image Analysis With Hierarchical Processing
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Solution Overview
Problem
Existing vehicle interior analysis systems require significant memory and computing resources due to independent operation of modules for different tasks, and are not scalable for different vehicle types and complexities.
Innovation Solution
A hierarchical data processing chain with image capturing and analysis modules that localize and extract information sequentially, storing data in a hierarchical database for efficient reuse, reducing resource usage and enabling scalability across various vehicle types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If independent image processing modules are used for each analysis task, then task-specific analysis accuracy is improved, but memory and computing capacity requirements increase significantly
Solution Approach 1:
The system segments the image processing into a hierarchical structure with a coarse analysis stage that localizes persons and objects first, followed by detailed analysis stages that focus only on regions of interest. This segmentation allows the system to maintain high analysis accuracy for specific tasks while reducing overall resource consumption by processing only relevant portions of images at high detail levels.
Solution Approach 2:
The patent introduces a hierarchical dimension to the processing architecture, organizing analysis tasks into multiple levels (coarse to fine). This dimensional organization allows the system to manage computational resources more efficiently by allocating detailed processing only where necessary, rather than applying uniform high-resolution processing across entire images.
2Measurement precision
If different systems are provided for different vehicle types, then analysis accuracy for specific vehicle interiors is improved, but system complexity and adaptability worsen
Solution Approach 1:
The patent creates a universal hierarchical processing framework that can be applied to different vehicle types (cars, trucks, buses, trains). The system uses vehicle-specific configuration data to adapt the same core processing architecture to various interior layouts and analysis requirements, eliminating the need for completely separate systems for each vehicle type while maintaining task-specific accuracy.
Solution Approach 2:
The system adjusts processing parameters such as region of interest coordinates, analysis thresholds, and hierarchical levels based on vehicle-type-specific configuration data. This allows the same processing framework to adapt to different vehicle interiors by changing parameters rather than requiring fundamentally different system architectures.
3Loss of information
If comprehensive detailed analysis is performed on all persons and objects, then information completeness is improved, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary coarse analysis to identify and localize persons and objects before conducting detailed analysis. This preliminary action creates a roadmap that guides subsequent detailed processing, ensuring that comprehensive information is gathered only from relevant regions rather than processing entire images at full detail, thus reducing processing time while maintaining information completeness.
Solution Approach 2:
The patent applies partial detailed analysis only to localized regions containing persons and objects of interest, rather than performing exhaustive analysis on entire images. This selective approach maintains information completeness for relevant targets while significantly reducing overall processing time and computational load.
Data Source
AI summary
The invention relates to a computer-implemented method for determining features of the interior (1) of a vehicle (2) with at least one image capturing unit (3), a data processing unit (4) and a database (5), comprising the capturing, by the image capturing unit (3), of a photo (11) or video of the interior (1) and transmission to the data processing unit (4), the analysis of the photo (11) or video in the data processing unit (4) by a sequential data processing chain (10) of program modules (12, 12′, 12″), comprising the steps of rough analysis for the localisation of persons and objects and generation of body and object images (15, 15′, 15″), detailed analysis of the body and object images (15, 15′, 15″), extraction of body and object data (7), and storage, by the data processing unit (4), of the determined body and object data (7) in a hierarchical data model (9) in the database (5).