18594331. GUIDED VEHICLE CAPTURE FOR VIRTUAL MODE GENERATION simplified abstract (STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY)
Contents
GUIDED VEHICLE CAPTURE FOR VIRTUAL MODE GENERATION
Organization Name
STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
Inventor(s)
Bryan R. Nussbaum of Bloomington IL (US)
Rebecca A. Little of Mesa AZ (US)
Kevin L. Mitchell of Tempe AZ (US)
Nathan C. Summers of Mesa AZ (US)
GUIDED VEHICLE CAPTURE FOR VIRTUAL MODE GENERATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18594331 titled 'GUIDED VEHICLE CAPTURE FOR VIRTUAL MODE GENERATION
Simplified Explanation: The patent application describes methods and systems for guiding user data capture during a vehicle scan using a mobile device. Users can scan a vehicle to generate a three-dimensional virtual model, with visual cues provided to indicate areas that need more scanning for data quality. Damage to vehicle components can be identified, directing additional data capture or user annotation.
Key Features and Innovation:
- User data capture guidance during vehicle scans using a mobile device
- Generation of three-dimensional virtual models from scan data
- Evaluation of models based on quality metrics
- Visual cues to indicate areas needing more scanning
- Identification of damage to vehicle components for further action
Potential Applications: This technology can be used in industries such as automotive, insurance, and vehicle maintenance for efficient data capture, damage assessment, and model generation.
Problems Solved:
- Ensuring comprehensive data capture during vehicle scans
- Providing guidance to users for optimal scanning results
- Identifying damage to vehicle components through generated models
Benefits:
- Improved accuracy in data capture for vehicle scans
- Enhanced user experience with visual cues and guidance
- Efficient damage identification and annotation for further action
Commercial Applications: "Mobile Device Guided Vehicle Scan Technology for Data Capture and Damage Identification" can be utilized by automotive manufacturers, insurance companies, and vehicle repair shops for streamlined data capture, accurate damage assessment, and improved customer service.
Prior Art: Prior art related to this technology may include patents or research on mobile device scanning technologies, three-dimensional modeling, and vehicle damage assessment tools.
Frequently Updated Research: Stay updated on advancements in mobile scanning technology, three-dimensional modeling algorithms, and automated damage identification systems for vehicles.
Questions about Mobile Device Guided Vehicle Scan Technology: 1. How does this technology improve the efficiency of data capture during vehicle scans? 2. What are the potential applications of this technology beyond vehicle scanning and damage identification?
Question 1: How does this technology improve the efficiency of data capture during vehicle scans? This technology provides users with visual cues and guidance during the scanning process, ensuring comprehensive data capture and efficient model generation.
Question 2: What are the potential applications of this technology beyond vehicle scanning and damage identification? This technology can also be applied in industries such as construction, architecture, and archaeology for site scanning, structural assessment, and historical preservation efforts.
Original Abstract Submitted
Methods and system for guiding user data capture during a scan of a vehicle using a mobile device are disclosed. A user may scan a vehicle using a camera or other sensors of the mobile device to capture data from which a three-dimensional virtual model may be generated. During the scanning process, models may be generated and evaluated according to quality metrics. Visual cues may be determined and presented to the user during scanning to indicate areas sufficiently scanned or areas requiring additional scanning to meet data quality requirements for model generation. Damage to vehicle components may be identified by analysis of the generated model, and addition data capture or user annotation entry may be directed based upon the identified damage.
