Person-of-Interest Image Search Interface with Concurrent Thumbnails
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Manual location and tracking of a person-of-interest in recorded video from multiple cameras is inefficient, necessitating automated search functionality in physical surveillance systems.
Innovation Solution
A method that concurrently displays face and body thumbnails of a person-of-interest alongside image search results, allowing for match confirmation and updating of search results, along with an appearance likelihood plot to facilitate efficient identification across a collection of video recordings from different cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated search functionality is implemented to identify persons-of-interest efficiently, then productivity is improved, but device complexity increases due to the need for multiple camera integration and automated processing systems
Solution Approach 1:
The system segments the search results into face thumbnails and body thumbnails displayed in separate regions of the interface. This segmentation allows operators to efficiently scan different types of visual information (faces vs. full bodies) in parallel, improving identification speed while keeping the interface organized and manageable
Solution Approach 2:
The system adds a spatial dimension to the search results by displaying multiple thumbnails simultaneously in a grid layout rather than sequentially. This dimensional change allows operators to compare multiple candidates across different cameras and time periods in a single view, significantly improving productivity without requiring complex sequential processing
2Loss of time
If multiple video recordings from different cameras are searched concurrently, then measurement precision is improved by reducing loss of time, but device complexity increases due to concurrent processing requirements
Solution Approach 1:
The system performs preliminary actions by automatically generating and displaying face thumbnails and body thumbnails from video recordings before the operator needs to identify the person-of-interest. The automated search functionality pre-processes multiple video streams, extracts relevant visual information, and organizes it into searchable thumbnails, eliminating the need for manual frame-by-frame review and significantly reducing time loss
Solution Approach 2:
The system creates visual copies of key information from multiple video recordings in the form of thumbnails. Instead of requiring operators to switch between multiple video feeds or review entire recordings, the system generates representative thumbnail copies that capture essential visual characteristics, allowing rapid comparison and identification across different cameras and time periods
3Ease of operation
If image search results are positioned according to likelihood of containing person-of-interest, then ease of operation is improved, but measurement precision requirements increase to accurately calculate and display likelihood rankings
Solution Approach 1:
The system performs preliminary likelihood calculations for each search result before display. By pre-computing relevance scores based on facial recognition confidence, temporal proximity, and spatial information, the system automatically sorts and positions thumbnails in descending order of likelihood. This preliminary ranking action significantly improves ease of operation, as operators can simply review results in order without needing to understand or evaluate complex matching algorithms
Solution Approach 2:
The system introduces an intermediary likelihood score that mediates between the complex multi-camera search algorithm and the operator's visual inspection. This intermediary metric translates complex processing results into a simple, intuitive ranking system where higher-positioned thumbnails have greater probability of containing the person-of-interest, improving ease of operation without requiring the operator to directly interpret complex measurement data
Data Source
AI summary
Methods, systems, and techniques for interfacing with a user to facilitate an image search for a person-of-interest. A face thumbnail of the person-of-interest, a body thumbnail of the person-of-interest, and image search results of the person-of-interest are concurrently displayed on a display to help a user identify the person-of-interest who appears in one or more of a collection of video recordings. The user may provide feedback to the system regarding whether image search results show the person-of-interest, which feedback may be used to refine the image search results.