Image Processor Seat Appearance Standardization for Occupant Detection
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Solution Overview
Problem
Conventional technologies for detecting the state of vehicle occupants require high costs due to the need for a large number of images taken from various camera mounting positions, leading to inefficiencies in distinguishing between seated and unseated states.
Innovation Solution
An image processor that transforms images based on a calculated transformation parameter, ensuring the appearance of the seat is standardized across different camera positions, allowing for the creation of a single learning model applicable to multiple mounting positions, reducing the need for extensive image datasets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large number of images are collected from various camera mounting positions to improve detection accuracy, then detection precision is improved, but system cost and complexity increase
Solution Approach 1:
The patent transforms images by changing parameters such as size, rotation angle, and position to create multiple views from a single camera position. This allows the system to achieve detection accuracy that would normally require multiple camera positions, thereby reducing system complexity while maintaining high detection precision.
Solution Approach 2:
The patent performs preliminary image transformation and normalization before detection. By pre-processing images to standardize seat appearances and generate multiple virtual views in advance, the system eliminates the need for physically installing multiple cameras at different positions, thus reducing device complexity while preserving detection accuracy.
2Measurement precision
If multiple learning models are created for different camera mounting positions to improve detection accuracy, then detection precision is improved, but processing time and computational resources increase
Solution Approach 1:
The patent creates a single universal learning model that can handle multiple camera mounting positions through image transformation. Instead of training separate models for each camera position, the system uses one model that processes transformed images representing different views, significantly reducing processing time while maintaining detection accuracy across all positions.
Solution Approach 2:
The patent generates multiple copied and transformed versions of single images to simulate different camera positions. These copied transformations (scaled, rotated, positioned variants) allow the learning model to learn from diverse perspectives without requiring multiple physical cameras or multiple separate learning models, thereby reducing computational overhead and processing time.
3Measurement precision
If images are collected and processed for each camera mounting position separately to improve detection accuracy, then detection precision is improved, but the time and resources required for image collection and processing increase
Solution Approach 1:
The patent merges the functionality of multiple camera positions into a single camera system by applying image transformations. Instead of collecting and processing images from multiple separate camera positions, the system collects images from one position and generates transformed versions that represent other positions, combining multiple processing tasks into one efficient workflow and improving productivity.
Solution Approach 2:
The patent changes image parameters (size, rotation, position) to generate multiple views from a single image capture. This approach eliminates the need for separate image collection and processing for each camera position, significantly improving processing efficiency while maintaining the detection accuracy that would otherwise require multiple physical cameras and separate processing pipelines.
Data Source
AI summary
An image processor includes an image converter. The image converter transforms data of an image that is photographed with a camera for photographing a seat, based on a transformation parameter that is calculated in accordance with a camera-position at which the camera is disposed. The image converter outputs the thus-transformed data of the image. The transformation parameter is a parameter for transforming the data of the image such that an appearance of the seat depicted in the image is approximated to a predetermined appearance of the seat.