Video Annotation Notification Relevance Filtering
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Solution Overview
Problem
Existing methods for annotating and distributing video content during film production are inefficient as they often result in irrelevant annotations being received by recipients due to manual filtering settings, leading to potentially relevant information being filtered out.
Innovation Solution
A method that selectively generates annotation notification alerts based on the difference in slate numbers and content complexity between the source and destination devices, determining relevance and content complexity to decide on display characteristics such as suppressing or highlighting annotations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If manual filtering settings are applied in the settings menu, then annotation notifications are reduced, but potentially relevant annotations are filtered out
Solution Approach 1:
The system automatically determines relevance between annotations and current video content without requiring manual user configuration. The device self-adjusts notification behavior by comparing slate numbers and determining relevance values, eliminating the need for users to manually configure filter settings while preventing loss of relevant annotations
Solution Approach 2:
The system dynamically changes the notification display state based on the calculated relevance value between annotation slate number and current video slate number. When relevance exceeds a threshold, notifications are displayed; otherwise they are suppressed, allowing the system to adaptively filter annotations based on content parameters rather than static manual settings
2Adaptability or versatility
If annotations are broadcast to all devices, then collaboration information is shared, but irrelevant annotations disrupt recipients
Solution Approach 1:
The system applies different notification handling to different devices based on their local context. Each device independently determines relevance by comparing its current video slate number with the annotation slate number, allowing annotations to be distributed universally while each recipient receives only locally relevant notifications
Solution Approach 2:
The notification display state is dynamic rather than static. The system continuously evaluates the relevance value between annotation and current video content, adjusting notification behavior in real-time as users switch between different video clips, ensuring annotations are displayed only when contextually appropriate
3Measurement precision
If slate number comparison is used to determine relevance, then notification accuracy is improved, but processing complexity increases
Solution Approach 1:
The system uses slate numbers as simplified copies or proxies for complex video content identification. Instead of analyzing actual video content similarity, the system compares numerical slate number identifiers, achieving accurate relevance determination through simple numerical comparison rather than complex content analysis
Data Source
AI summary
A method for selecting a display characteristic for a video annotation notification on a destination display device interconnected across a communications network to at least one source device that generates a video annotation includes receiving, determining, and selecting. An annotated video content is received from the at least one source device, wherein the annotated video content is associated with a source position in a video production hierarchy. A destination position is determined in the video production hierarchy for video content displayed on the destination display device. A correspondence is determined between the determined destination position and the source position associated with the annotated video content to define a relevance value. A content complexity value is determined based on the annotated video content. For the destination display device, one or more display characteristics of the video annotation notification is selected based on the relevance value and the determined content complexity value.