Video Thumbnail Reordering for Surveillance Identification
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Solution Overview
Problem
Camera surveillance systems face challenges in efficiently reviewing and identifying individuals or objects across multiple video recordings due to the cumbersome and time-consuming process of managing large numbers of video feeds from various cameras.
Innovation Solution
A method is implemented that displays thumbnails representing video recordings, organized in descending order of likelihood, allowing users to select and search for individuals or objects, with the system reordering and updating match likelihoods based on new information and user input, and enabling efficient identification and tracking across multiple camera feeds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple video feeds from various cameras are reviewed simultaneously during playback, then identification of individuals or objects of interest can be achieved, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The patent segments the video review process by organizing thumbnails into multiple sets, where each set corresponds to a specific time interval. This segmentation allows reviewers to focus on one time interval at a view, breaking down the overwhelming task of reviewing all video feeds simultaneously into manageable chunks organized by time periods
Solution Approach 2:
The system dynamically changes the parameter of thumbnail organization by reordering thumbnails within each time interval set based on updated match likelihoods. When new information becomes available (such as user selections or additional search results), the system recalculates and reorders thumbnails to reflect updated probabilities, optimizing the review process adaptively
2Productivity
If thumbnails are organized in descending order of match likelihood, then the most relevant video segments are prioritized for review, but the system requires continuous updating and reordering based on new information
Solution Approach 1:
The system performs preliminary ordering of thumbnails within each time interval set based on initial match likelihood calculations before the user begins reviewing. This preliminary organization provides an efficient starting point, with thumbnails already arranged to prioritize the most likely matches, reducing the initial cognitive load on reviewers
Solution Approach 2:
The system implements a feedback mechanism where user selections and new search results trigger recalculation of match likelihoods, which then feed back into the reordering process. This continuous feedback loop allows the system to adapt and improve its ordering based on actual review progress and newly discovered information
Data Source
AI summary
A method, system and computer program product for interactively identifying same individuals or objects present in video recordings is disclosed. When a thumbnail in a set of thumbnails is selected, new information is obtained. The new information may be that an individual or object is present in the portion of the video recording associated with the thumbnail. A search can be carried out for the individual or object based on the new information. The search generates new match likelihoods for each of displayed thumbnails within a user interface page. The displayed thumbnails are re-ordered based on the new match likelihoods.