Automated Videoconference Content Identification via Vector Matching

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Solution Overview

Problem

Existing videoconferencing technologies lack an efficient method to automatically identify and link content items presented during a meeting to the corresponding videoconference recordings, making it tedious and error-prone for users to review or track content usage.

Innovation Solution

A content management platform that processes videoconference recordings to classify frames, generate vector representations of content images, and match them to content items in a repository, thereby automating the identification and linking of content items to video recordings.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual identification of content items is used, then accuracy can be maintained, but time consumption and error rate increase significantly

Engineering Contradiction:

Improvecontent identification accuracyVSAvoidtime to review and track content

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs self-service by automatically analyzing videoconference recordings to identify content items without requiring manual intervention. The automated process extracts frames, generates vector representations, and matches them against content repositories, eliminating the need for users to manually review and track content while maintaining high accuracy through sophisticated image processing algorithms

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical processes with automated computational systems. Instead of humans visually reviewing and manually tracking content items, the system uses computer vision algorithms, vector space modeling, and automated matching mechanisms to perform these tasks, significantly reducing time consumption while maintaining precision through algorithmic accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automated content identification is implemented, then time efficiency improves, but system complexity increases

Engineering Contradiction:

Improvecontent identification efficiencyVSAvoidplatform architecture complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system segments the content identification process into distinct manageable stages: frame extraction from video, classification of frames as content-containing or non-content-containing, generation of vector representations, and matching against content repositories. This segmentation allows each component to be optimized independently and simplifies the overall system architecture while maintaining high productivity

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary vector representation layer that bridges the gap between raw video frames and content repository items. By converting visual frames into vector representations and using these as intermediaries for matching, the system simplifies the complexity of direct image comparison and enables efficient automated identification through standardized vector space operations

Inventive Principle:

Principle #24Intermediary (Mediator)

3Loss of information

If comprehensive content tracking is performed, then information availability improves, but computational resources required increase

Engineering Contradiction:

Improvecontent usage information availabilityVSAvoidcomputational resources consumed

Core Design Contradiction:

Loss of informationVSUse of energy by moving object

Solution Approach 1:

The system applies partial action by selectively processing only the portions of videoconference recordings that contain content information, rather than analyzing every frame uniformly. By first classifying frames as content-containing or non-content-containing and then processing only the relevant ones, the system reduces computational resource consumption while maintaining comprehensive information availability for tracked content items

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The patent changes the parameter representation from raw pixel data to vector representations, which transforms the computational task. By converting images into vector space representations and performing matching operations in this transformed space, the system reduces the computational complexity and energy requirements while maintaining the ability to track comprehensive content usage information

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250126226A1Automatic identification of content shared during videoconferences

Publication Date: 2025.04.17 HIGHSPOT

AI summary

A content management platform automatically identifies content items that are presented during videoconferences. The platform is configured to access a video file that contains a plurality of frames of a recording of a videoconference, where the recording of the videoconference contains a record of screen sharing by one or more participants in the videoconference. The platform can classify one or more of the frames as content-containing frames. For each of these content-containing frames, the platform generates a vector representation of an image of at least a portion of the respective frame. An image of a respective frame can then be matched to a selected content item from a content repository, based on a degree of similarity between the image of the frame and the content item. The platform can then store a representation that links the video file to the selected content item.