Spherical Video Highlight Detection via Audio Event Correlation
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Solution Overview
Problem
Existing video analysis systems fail to accurately identify video highlights based on audio events, as they lack effective methods to determine the temporal and spatial relationships between audio and visual content, leading to incomplete or incorrect highlight detection.
Innovation Solution
A system that processes video and audio information to identify audio events, determines their temporal and spatial types, and uses this information to pinpoint the moment and extent of highlight events within spherical video content, allowing for precise identification and storage of highlight moments and extents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If audio events are used to identify video highlights, then highlight detection accuracy is improved, but the complexity of determining temporal and spatial relationships increases
Solution Approach 1:
The system segments the video content into discrete highlight events by identifying distinct audio events and their corresponding temporal-spatial characteristics. Each audio event is processed independently to determine its temporal type (simultaneous, before, after) and spatial type (co-located, not co-located), allowing complex video analysis to be broken into manageable units that can be processed and stored as separate highlight records
Solution Approach 2:
The patent introduces audio events as an intermediary element that bridges audio and video content analysis. By using audio events as the mediating structure, the system can indirectly identify video highlights without requiring direct complex video analysis. The audio event serves as a mediator that carries temporal and spatial relationship information, simplifying the overall detection process while maintaining accuracy
2Measurement precision
If temporal and spatial types are determined for audio events, then highlight event identification precision is improved, but processing time increases
Solution Approach 1:
The system performs preliminary classification of audio events into temporal types (simultaneous, before, after) and spatial types (co-located, not co-located) during the initial processing stage. By determining these characteristics upfront rather than during final highlight generation, the system avoids repeated complex calculations and reduces overall processing time while maintaining identification precision
3Measurement precision
If audio event extent and highlight event extent are identified, then spatial accuracy of highlight detection is improved, but computational requirements increase
Solution Approach 1:
The system applies local quality analysis by determining audio event extent and highlight event extent only for specific regions of interest within the video content. Rather than analyzing the entire video uniformly, the system focuses computational resources on local spatial relationships where audio events occur, calculating extents only for relevant temporal and spatial segments, thereby reducing overall computational requirements while maintaining spatial accuracy
Data Source
AI summary
Audio content may be captured during capture of spherical video content. An audio event within the audio content may indicate an occurrence of a highlight event based on sound(s) originating from audio source(s) captured within an audio event extent within the spherical video content at an audio event moment. Temporal type of the audio event providing guidance with respect to relative temporality of the highlight event with respect to the audio event and spatial type of the audio event providing guidance with respect to relative spatiality of the highlight event with respect to the audio event may be determined. A highlight event moment of the highlight event may be identified based on the audio event moment and temporal type of the audio event. A highlight event extent of the highlight event may be identified based on the audio event extent and the spatial type of the audio event.