Video Annotation Engine for Automated Form Population
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Solution Overview
Problem
Existing video annotation systems often include irrelevant information, wasting time for users searching for specific details, particularly in scenarios like investigating traffic accidents where only relevant annotations are needed to complete reports or forms.
Innovation Solution
A method and apparatus that utilize a video analysis engine to identify and annotate specific objects or scenes within videos based on text input from forms, such as traffic reports, populating form fields with determined characteristics like make and model of vehicles, and selectively annotating only relevant information based on user-filled fields.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If video annotation systems annotate all detected objects and information, then the annotation completeness is improved, but the time required for users to find relevant information increases
Solution Approach 1:
The system performs preliminary actions by pre-populating form fields with data extracted from video analysis before the user needs the information. The video analysis engine automatically identifies objects, scenes, and characteristics, and populates corresponding form fields in advance, so users receive ready-to-use information without needing to search through comprehensive annotations.
Solution Approach 2:
The system extracts only the specific information needed for form completion from the video content. Instead of annotating all detected objects, the video analysis engine selectively extracts characteristics relevant to the form fields (such as vehicle make, model, color, license plate) and presents only this extracted information to users, filtering out irrelevant annotations.
2Measurement precision
If the video analysis engine analyzes all video content to populate form fields, then the data accuracy is improved, but the processing time increases
Solution Approach 1:
The system performs preliminary analysis by pre-processing video content to identify and extract relevant characteristics before form completion is needed. The video analysis engine continuously analyzes video frames in the background, pre-identifying objects and their attributes, so when form population is required, the analysis is already complete or near-complete, reducing the perceived processing time while maintaining accuracy.
Solution Approach 2:
The system applies partial action by analyzing only the portions of video content that are relevant to the specific form fields that need population. Instead of exhaustively analyzing every frame for every possible characteristic, the engine selectively applies analysis based on the form requirements, performing sufficient analysis to achieve accurate population without unnecessary excessive processing.
3Productivity
If the system populates all form fields automatically, then the productivity is improved, but the complexity of the system increases
Solution Approach 1:
The system implements self-service by enabling automatic population of form fields through integrated video analysis capabilities. The video analysis engine autonomously identifies objects and characteristics in video content, extracts relevant data, and populates corresponding form fields without requiring manual intervention, allowing the system to serve itself in the data collection and form completion process.
Solution Approach 2:
The system achieves universality by designing a multi-functional video analysis engine that can perform multiple tasks: detecting objects, identifying characteristics, extracting text, and populating various types of form fields. This single integrated engine handles diverse analysis requirements across different video content and form types, reducing the need for separate specialized systems while maintaining high productivity.
Data Source
AI summary
A method and apparatus for annotating video is provided herein. During the process of annotating a video, important text within a form is identified. Annotations are placed within the video that are related to the important text within the form. In addition to annotating the video with important text taken from the form, Information that is determined based on the text, may be taken from the video in order to help fill the form.