Full Motion Video Photogrammetric Reconstruction System
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Solution Overview
Problem
Current methods for processing Full Motion Video (FMV) data into accurate 3-D models are hindered by the costly and time-consuming manual frame selection process, lack of automated technologies for filtering relevant frames, and inability to address anomalies in real-time.
Innovation Solution
An intelligent system that uses interpolation processes and algorithmic selection to rapidly process FMV data, performing geometric calculations and filtering to produce highly accurate 2-D and 3-D images in real-time, with virtual processing components for data parsing, metadata extraction, and filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual frame selection is used to filter relevant frames, then frame selection accuracy is improved, but processing time and cost increase significantly
Solution Approach 1:
The system performs self-service by automatically selecting relevant frames through algorithmic analysis of motion vectors, metadata, and image content. The frame selection process does not require human intervention - the system autonomously evaluates candidate frames using computational criteria to identify frames containing target objects, thereby eliminating manual processing time while maintaining selection accuracy through multiple validation checks
Solution Approach 2:
The patent replaces the mechanical/manual frame selection process with an automated computational system. Instead of human technicians manually reviewing frames, the system uses algorithms that analyze motion vectors, metadata, and image content to automatically identify and select relevant frames, substituting human cognitive processing with automated image analysis and pattern recognition
2Measurement precision
If manual frame selection is used to filter relevant frames, then frame selection quality is improved, but productivity decreases
Solution Approach 1:
The system autonomously performs frame selection without human intervention, evaluating candidate frames through algorithmic analysis of motion vectors, metadata, and image content. This self-service capability enables the system to process vast volumes of video data at high speed while maintaining consistent selection quality through automated validation, thereby dramatically increasing productivity compared to manual processes
Solution Approach 2:
The patent employs parameter-based filtering by analyzing multiple parameters including motion vector magnitude, metadata quality indicators, and image content features. By changing from manual subjective assessment to automated parameter evaluation, the system can rapidly process frames through defined thresholds and criteria, maintaining selection quality while enabling high-throughput processing of large video datasets
3Productivity
If automated frame selection is implemented, then processing speed is improved, but ability to detect and filter relevant frames deteriorates
Solution Approach 1:
The system replaces manual frame review with automated analysis using multiple computational methods including motion vector analysis, metadata parsing, and image content evaluation. This substitution enables rapid processing speed while maintaining detection accuracy through the combined use of multiple analysis techniques that validate frame relevance through objective computational criteria rather than subjective human judgment
Solution Approach 2:
The system performs preliminary analysis of candidate frames by examining motion vectors and metadata before full processing. This preliminary action allows the system to quickly identify and filter out irrelevant frames at high speed, then apply more rigorous analysis only to promising candidates, thereby maintaining both processing speed and detection accuracy through a staged evaluation process
4Loss of time
If real-time processing is implemented, then response time is improved, but ability to address data anomalies deteriorates
Solution Approach 1:
The system performs preliminary validation of data quality by examining metadata and motion vectors before full processing. This preliminary action enables real-time detection of anomalies such as corrupted metadata or impossible motion patterns, allowing the system to flag or exclude problematic frames immediately without delaying the overall real-time processing pipeline
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor processing results and data quality metrics in real-time. By analyzing the output of each processing stage and comparing it against expected parameters, the system can detect anomalies and adjust processing accordingly, maintaining both real-time response and reliable anomaly detection through continuous feedback loops
Data Source
AI summary
This invention is a system for photogrammetric analysis of full motion video (FMV), which converts FMV to image files, extracts metadata, and produces accurate 2-D and 3-D geospatial images in real time.