Video Query Contextualization Router Model
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Solution Overview
Problem
Existing technologies struggle to efficiently process video queries, as text searching alone may not provide desired results due to the difficulty in determining appropriate search terms, and screen capture methods are tedious and do not capture the full sequence of interest.
Innovation Solution
A computing system that processes video queries using a machine-learned router model, which generates a video clip and routing data from the input query and video data, allowing for the determination of relevant processing systems to provide search results without navigating away from video playback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If text searching is used to process video queries, then search capability is provided, but search accuracy deteriorates due to difficulty in determining appropriate search terms
Solution Approach 1:
The patent introduces an intermediary system that captures video frames and uses AI models to generate descriptive text from visual content. This intermediary translates video content into searchable text descriptions, allowing users to search based on what they see rather than requiring them to formulate precise text queries beforehand. The system acts as a mediator between visual content and text-based search.
Solution Approach 2:
Instead of the traditional approach where text queries are converted to search results, the patent inverts the process by first capturing video content, generating text descriptions from the video frames using AI, and then performing search operations on these generated descriptions. This reversal allows the system to understand user intent based on visual context rather than relying on user-generated text queries.
2Loss of information
If screen capture method is used to provide video context, then video information is obtained, but operational complexity increases due to tedious navigation requirements
Solution Approach 1:
The system performs automatic screen capture and video frame extraction without requiring user intervention. The AI model automatically captures relevant video frames, generates descriptions, and performs search operations in the background. Users simply need to provide a query, and the system handles all the complex steps of video analysis and information retrieval autonomously.
Solution Approach 2:
The patent implements preliminary processing of video content by pre-generating text descriptions from video frames and storing them for quick retrieval. This preliminary action prepares the video data in advance, so when a user queries, the system can quickly match against pre-processed information without requiring complex real-time analysis or user navigation through video content.
3Speed
If single image is used for query processing, then quick processing is achieved, but information completeness deteriorates as full sequence is not captured
Solution Approach 1:
The patent segments the video into multiple frames and processes them individually or in small groups. Instead of analyzing the entire video sequence at once (which would be slow), the system divides it into manageable frame segments, generates descriptions for each, and combines results. This segmentation enables faster processing while preserving sequence information through the aggregation of frame-level analyses.
4Measurement precision
If comprehensive video processing is performed, then search accuracy improves, but computational cost increases
Solution Approach 1:
The system performs partial processing by selecting and analyzing only the most relevant video frames rather than processing every frame in the video. The AI model identifies key frames that contain the most information and focuses computational resources on those, achieving good search accuracy without the excessive computational cost of analyzing the entire video sequence in detail.
Data Source
AI summary
Systems and methods for video query contextualization can include a router model that determines how to process and respond to the query associated with the video. The systems and methods can include obtaining an input query and video data, processing the input query and the video data with the router model to generate a video clip and routing data, and the routing data can then be utilized to determine which processing system to utilize to process the video clip and the input query. The video clip can then be processed with the determined processing system to generate a query response that may be provided to the user.