Contextual Video Search via Tool Interaction Detection
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Solution Overview
Problem
Users face difficulties in finding relevant portions of lengthy and unstructured video instruction guides within interactive computing environments, as existing methods lack context in video searching, making it hard to identify specific segments related to their tasks.
Innovation Solution
The system detects user interactions with content creation tools, updates video search queries with context information, and performs searches on video captions to rank relevant segments, providing users with direct access to relevant video clips.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If video instruction guides are made lengthy and comprehensive to cover all tasks, then the coverage and completeness of instructions improve, but the difficulty of finding specific relevant segments increases
Solution Approach 1:
The system performs preliminary actions by automatically generating captions for video segments before user search, and by pre-organizing video content into searchable segments with associated metadata. This allows the comprehensive video content to be quickly searched and navigated when users need specific information.
Solution Approach 2:
The system introduces an intermediary search interface that mediates between the user and the comprehensive video content. The search interface accepts user queries, matches them against captioned video segments, and retrieves relevant portions, thereby enabling efficient navigation through lengthy video guides without requiring users to manually browse entire videos.
2Ease of operation
If traditional video navigation interfaces are used, then the simplicity of the interface is maintained, but the precision of locating specific task-related content deteriorates
Solution Approach 1:
The system replaces the mechanical interaction of manual video navigation (scrubbing through timelines, skipping segments) with an automated information retrieval system. Users input natural language queries about their tasks, and the system automatically retrieves the precise video segments containing relevant instructions, eliminating the need for manual navigation while maintaining interface simplicity.
Solution Approach 2:
The system enables self-service by automatically analyzing user queries and independently retrieving relevant video segments without requiring users to manually navigate or search through video content. The system serves itself by using its own captioned video database to answer user questions about specific tasks.
3Speed
If video summaries are used to identify content, then the speed of accessing video information improves, but the accuracy of identifying relevant segments deteriorates due to lack of context
Solution Approach 1:
The system segments video content into discrete, captioned portions that can be individually searched and retrieved. Each video segment is associated with specific captions describing its content, allowing the system to quickly identify and retrieve only the segments relevant to user queries while maintaining high accuracy through context-rich captioning.
Solution Approach 2:
The system changes the parameter of video representation from continuous playback to discrete captioned segments with associated metadata. This transformation allows the system to search and retrieve video content based on semantic parameters (task descriptions, tool names, actions) rather than temporal parameters, thereby improving both speed and accuracy of segment identification.
Data Source
AI summary
A method includes detecting control of an active content creation tool of an interactive computing system in response to a user input received at a user interface of the interactive computing system. The method also includes automatically updating a video search query based on the detected control of the active content creation tool to include context information about the active content creation tool. Further, the method includes performing a video search of video captions from a video database using the video search query and providing search results of the video search to the user interface of the interactive computing system.