Context-Sensitive Video Content Insertion System
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Solution Overview
Problem
Current video streaming and hosting platforms face challenges in providing non-intrusive and relevant content insertion methods, such as advertisements and recommendations, which disrupt the user experience and fail to effectively reach the target audience.
Innovation Solution
A system and method for strategic content insertion into videos using images, logos, QR codes, or hyperlinks, analyzing multiple modalities like metadata, audio, and user profiles to determine relevant content and suitable insertion locations, ensuring a seamless and user-centric experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If video advertisements are inserted to generate revenue, then the platform can earn income, but the user experience deteriorates due to interruptions and the ads may not reach the target audience effectively
Solution Approach 1:
The patent applies local quality by inserting advertisements at specific local positions within the video content rather than as separate interruptions. The system identifies homogeneous regions in video frames and inserts ads locally within these regions, making the advertisement experience integrated into the content flow rather than disruptive to the overall user experience.
Solution Approach 2:
The patent merges the advertisement content with the main video content by inserting ads within the video stream itself. Instead of separating ads from content, the system combines them by placing ads in homogeneous regions of video frames, creating a unified viewing experience where ads become part of the video narrative.
2Loss of information
If relevant content is provided as recommendations outside the frame, then users can access additional information, but users must manually search and select content which disrupts viewing
Solution Approach 1:
The patent implements self-service by having the system automatically identify and insert relevant content within the video frame without requiring user intervention. The system autonomously analyzes video content, identifies homogeneous regions, and places relevant information or recommendations directly in the video stream, eliminating the need for users to manually search or navigate external recommendations.
Solution Approach 2:
The patent applies preliminary action by pre-identifying and inserting relevant content into the video stream before the user views it. The system analyzes the video content in advance, determines appropriate insertion points with homogeneous regions, and prepares the enriched video content beforehand, so that relevant information is already positioned and ready for user consumption without requiring real-time user search or selection.
3Reliability
If students pause video to look up relevant content, then they can understand concepts better, but the learning flow is interrupted and efficiency decreases
Solution Approach 1:
The patent merges supplementary educational content with the main video lecture by inserting additional notes, explanations, or related concepts directly within the video frame during playback. This integration allows students to access supporting material without leaving the video flow, combining the lecture content with auxiliary learning resources in a unified viewing experience.
Solution Approach 2:
The patent applies local quality by inserting educational supplements at specific local positions within the video content where they are most relevant. The system identifies appropriate regions in video frames and places supplementary information locally near related content, allowing students to understand concepts better while maintaining the continuous learning flow without interruptions.
4Loss of information
If ads are made more prominent to increase visibility, then advertising effectiveness improves, but intrusiveness increases and user satisfaction decreases
Solution Approach 1:
The patent applies local quality by inserting advertisements in specific local homogeneous regions of video frames where they can be visible without dominating the overall content. The system carefully selects insertion positions that provide adequate visibility for advertising effectiveness while maintaining the natural flow and aesthetic of the video, avoiding excessive prominence that would cause intrusiveness.
Data Source
AI summary
Described herein is a method and system for automated, context sensitive and non-intrusive insertion of consumer-adaptive content in video. It assesses ‘context’ in the video that a consumer is viewing through multiple modalities and metadata about the video. The method and system described herein analyzes relevance for a consumer based on multiple factors such as the profile information of the end-user, history of the content, social media and consumer interests and professional or educational background, through patterns from multiple sources. The system also implements local-context through search techniques for localizing sufficiently large, homogenous regions in the image that do not obfuscate protagonists or objects in focus but are viable candidate regions for insertion for the intended content. This makes relevant, curated content available to a user in the most effortless manner without hampering the viewing experience of the main video.