Cognitive Video Navigation Aid for Viewer Interest Matching
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Solution Overview
Problem
Current methods for accessing specific portions of pre-recorded video presentations do not consider the viewer's interests or emotional state, making it inefficient to navigate and watch relevant content at optimal times.
Innovation Solution
A cognitive system performs semantic and sentiment analysis on both the video content and the viewer to create a navigation aid that recommends relevant sections based on interest and emotional state, with dynamic entry and exit pointers adjusting to the viewer's time and emotional state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If semantic and sentiment analysis are performed on video content and viewer to create personalized navigation aid, then viewing efficiency and relevance are improved, but system complexity and computational requirements increase
Solution Approach 1:
The system performs semantic analysis and sentiment analysis of the video content in advance before the viewer watches, creating a pre-computed navigation aid with topic indices, speaker indices, and sentiment markers. This preliminary processing allows the viewer to quickly navigate to relevant sections without real-time analysis delays, improving viewing efficiency while managing system complexity through batch processing.
Solution Approach 2:
The patent introduces an intermediary navigation aid layer between the raw video content and the viewer. This navigation aid includes topic-based indices, speaker-based indices, and sentiment-based markers that mediate between the complex video content and the viewer's information needs, allowing efficient navigation without requiring the viewer to directly interact with the full video content.
2Adaptability or versatility
If dynamic entry and exit pointers are generated based on viewer's emotional state and time of day, then content relevance and viewer engagement are improved, but computational overhead and processing time increase
Solution Approach 1:
The system pre-computes multiple navigation scenarios based on different emotional states and times of day during the initial analysis phase. These pre-computed navigation paths are stored and can be quickly retrieved based on the viewer's current state, avoiding real-time computation of entry and exit pointers and reducing processing time while maintaining adaptability.
Solution Approach 2:
The patent changes the parameters of the navigation aid dynamically based on viewer state. Instead of regenerating the entire navigation structure, the system adjusts specific parameters such as entry points, exit points, and recommended sections based on detected emotional state and time of day, allowing quick adaptation with minimal computational overhead.
3Measurement precision
If continuous sentiment analysis of the viewer is performed to update the navigation aid, then personalization accuracy is improved, but energy consumption and computational resources increase
Solution Approach 1:
The system performs sentiment analysis of the viewer at periodic intervals rather than continuously, updating the navigation aid at predetermined checkpoints during video playback. This periodic approach maintains reasonable personalization accuracy while significantly reducing energy consumption and computational resource requirements compared to continuous real-time analysis.
Solution Approach 2:
The patent applies sentiment analysis selectively to key moments or sections of the video rather than uniformly across the entire viewing experience. By focusing computational resources on critical decision points where navigation decisions are most impactful, the system achieves adequate personalization accuracy with reduced overall energy consumption.
Data Source
AI summary
A cognitive system and method for optimized video playback. A semantic and sentiment analysis of the video presentation is performed to identify one or more topics, speakers, and sentiments therein. An analysis of at least one viewer is performed to identify the topics, speakers, and sentiments of interest. The topics, speakers, and sentiments are associated with a time-based mapping of the video presentation based on the analysis of the viewer. A navigation aid for the video presentation is generated using the time-based mapping, wherein the navigation aid includes entry and exit pointers to portions of the video presentation that match the viewer's areas of interest. Portions of the video presentation may be recommended and displayed to the viewer using the navigation aid.