Key Moment Detection for Video Ad Timing
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Solution Overview
Problem
Advertisers and content owners face inefficiencies in delivering targeted advertisements and interactive content due to the inability to automatically detect key moments in videos, leading to wasted ad budgets and mismatched content presentation.
Innovation Solution
A system comprising a key signals detector module, a key moments machine learning module, and a match detector module that analyzes videos to identify key signals and moments, using machine learning and viewer feedback to optimize content display based on demographic information and video metadata.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If demographic studies and assumptions about typical audience are used to target advertisements, then advertisers can reach a larger audience with their ads, but much of the ad budget is wasted because the target audience is not interested in the ad or the timing is incorrect
Solution Approach 1:
The system performs preliminary analysis of video content to detect key moments and signals before ad delivery. By pre-processing the video content to identify emotionally significant segments, the system prepares targeted ad placements in advance, ensuring ads are delivered at optimal moments when audience engagement is highest, thereby reducing wasted ad budget.
Solution Approach 2:
The system implements feedback mechanisms by analyzing viewer responses and engagement metrics in real-time. This feedback loop allows the system to continuously optimize ad timing and targeting based on actual audience reactions, adjusting future ad placements to maximize budget effectiveness and minimize waste.
2Loss of energy
If automated key moment detection is implemented to optimize ad timing, then ad budget efficiency improves, but system complexity increases due to multiple detection modules and machine learning components
Solution Approach 1:
The system segments the complex task of ad optimization into distinct functional modules: key signals detector module for identifying emotional cues, key moments machine learning module for temporal analysis, and match detector module for ad placement decisions. This segmentation allows each module to specialize in specific functions, making the overall complex system more manageable and maintainable.
Solution Approach 2:
The key moments machine learning module serves as an intermediary between the key signals detector and the match detector. It processes and translates raw emotional signals into actionable temporal markers that guide ad placement decisions, simplifying the interface between detection and decision-making components.
3Adaptability or versatility
If real-time key moment detection is performed to enable timely content delivery, then content relevance improves, but processing time and computational resources increase
Solution Approach 1:
The system applies local quality analysis by focusing computational resources on detecting specific key signals and moments that are most relevant to ad placement, rather than analyzing the entire video uniformly. This selective approach concentrates processing power on emotionally significant segments, improving relevance while reducing overall processing time.
Data Source
AI summary
A system for automatically displaying content based on key moments includes: rules and database; a key moments machine learning module connected with at least one match detector module of at least one external entity; a key signals detector module connected with at least one content owner, the rules and database; and the key moments machine learning module; and a viewer connected with the at least one match detector module. The key signals detector module is configured to receive a video from at least one of the at least one content owner, and detect at least one key signal in the video. The key moments machine learning module is configured to receive the detected at least one key signal and detect at least one key moment; and at least one of the at least one match detector module is configured to receive the detected at least one key moment and decide when to display the content to the viewer.