Vehicle Image Capture Guidance via 3D Model Overlays
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Solution Overview
Problem
Existing methods for capturing images or videos of vehicles lack accuracy and completeness, particularly in online auctions where in-person inspection is not possible, leading to incomplete vehicle condition reports and potential missed vehicle defects.
Innovation Solution
A system and method using computer hardware processors to generate a part-annotated 3D model of a vehicle, specify portions to be imaged, and create overlays to guide users in capturing high-quality images or videos of the vehicle, ensuring relevant parts are properly captured and analyzed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a user captures images of a vehicle without guidance, then the capture process is simple and quick, but the accuracy and completeness of the captured vehicle condition data is poor
Solution Approach 1:
The patent segments the vehicle into multiple parts (exterior, interior, engine, etc.) and divides the image capture process into multiple standardized views for each part. The system provides guidance for capturing specific portions of the vehicle from predetermined angles and positions, ensuring comprehensive coverage without requiring the user to capture every possible angle manually.
Solution Approach 2:
The system provides real-time feedback to the user during the image capture process by displaying overlays that show the current camera position relative to the required view. The system compares the captured image with the reference view and provides guidance on whether the image meets the required standards, allowing users to adjust their capture accordingly.
2Loss of information
If a user captures images without standardized guidance, then the capture process is fast, but the completeness of vehicle condition reports is insufficient
Solution Approach 1:
The system performs preliminary action by pre-defining the standardized views and required capture parameters for each vehicle part before the user begins capturing images. The system provides a checklist and guidance instructions in advance, so the user knows exactly what needs to be captured and in what order, reducing the time needed during actual capture.
Solution Approach 2:
The patent introduces a dimensional approach by capturing images from multiple predetermined angles and positions for each vehicle part. Instead of requiring the user to manually determine all necessary views, the system provides guidance in multiple dimensions (front, side, rear, top, bottom views) to ensure comprehensive coverage of the vehicle condition.
3Measurement precision
If the system provides detailed guidance for capturing all vehicle parts, then the accuracy of vehicle condition data is high, but the complexity of the guidance system increases
Solution Approach 1:
The system applies local quality by providing detailed guidance only for specific critical parts of the vehicle that require thorough inspection, while using simpler guidance for less critical areas. The guidance level is customized according to the importance and complexity of each vehicle part, ensuring high accuracy where needed without unnecessarily complicating the entire system.
Solution Approach 2:
The system uses copying by providing reference images and overlays that replicate the ideal view of each vehicle part. Instead of requiring the user to understand complex geometric requirements, the system provides visual copies of the reference views that users can directly compare with their captures, simplifying the guidance while maintaining high accuracy.
4Measurement precision
If the system analyzes all captured images thoroughly, then the quality of vehicle condition reports is high, but the processing time and computational resources increase
Solution Approach 1:
The system extracts and focuses analysis only on the most critical vehicle parts and features that directly impact the condition assessment. By identifying and prioritizing the most important areas for inspection, the system can provide thorough analysis of key components without unnecessarily processing every detail of every image, thus maintaining report quality while improving processing speed.
Solution Approach 2:
The system replaces manual, time-consuming image analysis with automated computer vision and machine learning algorithms. The system uses algorithms to automatically detect, measure, and assess vehicle conditions from the captured images, significantly reducing the time and computational resources required compared to manual inspection while maintaining or improving the quality of the condition reports.
Data Source
AI summary
Techniques guiding users in capturing vehicle images and video are provided. Some techniques involve: obtaining a three-dimensional model of a vehicle; generating a part-annotated 3D model of the vehicle; obtaining portions of the vehicle to be imaged by the user; generating overlays corresponding to the portions of the vehicle to be imaged by the user; and outputting the overlays for use in guiding the capturing images of the vehicle. Some techniques involve: obtaining a video of a vehicle; obtaining frames from the video; analyzing the frames to identify portions of the vehicle the user is to video, the analyzing comprising for each particular frame: determining whether the particular frame complies with one or more image quality criteria; and identifying at least one portion of the vehicle captured in the particular frame; and generating instructions for guiding the user to video the identified portions of the vehicle.