Video Frame OCR Extraction for Searchable Meeting Text
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Solution Overview
Problem
Existing digital communication platforms lack the ability to automatically extract textual content from video recordings of communication sessions, making it difficult and time-consuming to analyze and search for specific information, particularly presentation slides and titles, during sales meetings or other remote interactions.
Innovation Solution
A system that receives video content, extracts frames, classifies them based on image analysis, identifies frames containing text, detects titles within these frames using optical character recognition (OCR), and transmits the extracted textual content and titles to client devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual scrolling and searching through video recordings is used to find textual content, then no additional processing is required, but the time and effort spent on analysis is excessive
Solution Approach 1:
The patent replaces the mechanical manual searching process with an automated optical character recognition (OCR) system. The OCR technology automatically extracts and transcribes textual content from video frames, substituting human manual effort with machine-based optical recognition and text processing capabilities.
Solution Approach 2:
The system enables self-service by automatically extracting, transcribing, and making searchable the textual content from video recordings without requiring user intervention. The OCR system independently processes video frames, identifies text regions, extracts characters, and creates searchable indexes, allowing users to immediately search and retrieve information.
2Ease of operation
If automated text extraction systems are implemented, then search capabilities are improved, but system complexity increases
Solution Approach 1:
The patent segments the text extraction process into distinct modular components: video frame extraction, OCR processing, text region identification, character extraction, and index creation. Each module handles a specific aspect of the process, making the overall complex system manageable through functional decomposition and independent optimization of each segment.
Solution Approach 2:
The patent introduces an intermediary indexing system that bridges the gap between raw video content and user search queries. The extracted textual content is stored in a searchable index structure that acts as a mediator, allowing users to search for information without directly processing or analyzing video frames, thus simplifying the user interface while maintaining powerful search capabilities.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient extraction and transmission of textual content from video frames, improving the analysis and search capabilities of communication session recordings, enhancing sales performance by reducing the time spent on manual scrolling and searching.
Implementation Method 1
extracts, via optical character recognition (OCR), the title from the cropped title area of the frame
Data Source
AI summary
In one embodiment, the system receives video content of a communication session with participants. The system then extracts high-resolution versions and low-resolution versions of frames from the video content, and classifies the low-resolution frames of the video content based on identifying text within the low-resolution frames. The system identifies one or more low-resolution distinguishing frames containing text. For each low-resolution distinguishing frame containing text, the system detects a title within the frame, crops a title area with the title within the frame, and extracts, via optical character recognition (“OCR”), the title from the cropped title area of the high-resolution version of the frame. The system extracts, via OCR, textual content from the high-resolution versions of the low-resolution distinguishing frames containing text, and then transmits the extracted textual content and extracted titles to one or more client devices.