Video Object Insertion Classification via Attention Proximity
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Solution Overview
Problem
The process of identifying and evaluating suitable opportunities for digital object insertion in videos is inefficient and inconsistent, particularly for long videos like films, due to the time-consuming and labor-intensive nature of human evaluation, which can lead to resource inefficiencies and subjective analysis inconsistencies.
Innovation Solution
A computer-implemented method that analyzes pixels in video frames to identify potential object insertion opportunities, determines a proximity value based on the distance between these opportunities and the focus of attention, and classifies them using AI algorithms trained on a corpus of images, enabling efficient and consistent classification of candidate and rejected opportunities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human operators manually evaluate each identified object insertion opportunity, then the evaluation can be performed with human judgment and flexibility, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
An automated analysis system acts as an intermediary between the video content and human operators. The system analyzes pixel data, identifies potential object insertion opportunities, determines focus of attention regions, calculates proximity values, and classifies opportunities automatically. This intermediary processing filters and prioritizes opportunities before human review, reducing the time and labor required while maintaining evaluation quality through a combination of automated objective analysis and human subjective judgment.
2Adaptability or versatility
If human operators evaluate object insertion opportunities, then subjective analysis can be performed, but inconsistencies arise between different operators and even from the same operator at different times
Solution Approach 1:
The automated analysis system serves as a consistent intermediary that applies uniform algorithms for identifying object insertion opportunities, determining focus of attention, calculating proximity values, and classifying opportunities. This standardized automated process eliminates variability between different human operators and ensures consistent evaluation criteria are applied across all video content, while still allowing human operators to perform flexible subjective analysis on the prioritized opportunities.
Solution Approach 2:
The patent replaces the mechanical process of human visual inspection and subjective judgment with an automated computer-based analysis system. The system uses pixel analysis, focus of attention determination, and proximity value calculation algorithms to objectively evaluate object insertion opportunities. This substitution of mechanical human evaluation with automated computational analysis ensures consistent, repeatable, and reliable results while maintaining the ability to perform flexible creative assessment.
3Reliability
If all identified object insertion opportunities are reviewed, then no suitable opportunities are missed, but resource efficiency decreases particularly for long videos
Solution Approach 1:
The automated analysis system extracts and identifies all potential object insertion opportunities from the video content by analyzing pixels, determining focus of attention regions, and calculating proximity values. This comprehensive extraction ensures no suitable opportunities are missed, as the system systematically evaluates the entire video content. The extracted opportunities are then classified and prioritized, allowing human operators to focus resources on the most promising candidates rather than reviewing every single opportunity, thus improving resource efficiency while maintaining completeness.
Solution Approach 2:
The system performs preliminary automated analysis of all object insertion opportunities before human review. It pre-identifies potential opportunities, determines their proximity to focus of attention, and classifies them according to established criteria. This preliminary action filters and prioritizes opportunities in advance, ensuring comprehensive identification while enabling efficient human resource allocation by presenting only the most suitable candidates for detailed evaluation and selection.
Data Source
AI summary
The present disclosure relates to a computer implemented method, computer program and apparatus for classifying object insertion opportunities in a video by identifying at least one object insertion opportunity in a scene of the video, identifying a focus of attention in the scene, determining a proximity value for each of the at least one object insertion opportunity based at least in part on the object insertion opportunity and the focus of attention, wherein the proximity value is indicative of a distance between the respective at least one object insertion opportunity and the focus of attention in the scene, and classifying each of the at least one object insertion opportunity based at least in part on the proximity value determined for each respective at least one object insertion opportunity.