Iterative Appearance Search for Video Object Detection
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Solution Overview
Problem
Existing automated security systems require manual review of video footage by security personnel to detect and classify visual objects of interest, which is time-consuming and inefficient, especially in large areas like shopping malls.
Innovation Solution
A computer-implemented method and system that employs iterative appearance searching using computer vision-driven techniques. The system inputs a first reference image without the missing object, performs an initial appearance search across multiple security cameras, obtains a second reference image with the missing object from the search results, and then performs a second appearance search without user intervention, displaying results when the search is successful.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual review of video footage is performed by security personnel, then object detection and classification can be performed, but the process is time-consuming and inefficient
Solution Approach 1:
The system performs self-service by automatically executing appearance searches across video data without requiring continuous human intervention. The computer vision system independently processes reference images, searches through video footage, and generates results, freeing security personnel from manual review tasks while maintaining detection effectiveness
Solution Approach 2:
The patent replaces the mechanical manual review process with an automated computer vision system. The system uses image processing algorithms, feature extraction, and pattern recognition to detect and classify objects in video footage, substituting human observational and cognitive functions with automated computational processes
2Loss of time
If iterative appearance searching is performed automatically, then time required to locate objects is reduced, but system complexity increases
Solution Approach 1:
The appearance search process is segmented into distinct operational phases: reference image input, video data searching, result generation, and iterative refinement. Each phase is handled by specialized modules within the computer vision system, making the overall complex process manageable and systematic through functional decomposition
Solution Approach 2:
The system incorporates feedback mechanisms where search results from one iteration become reference images for subsequent iterations. The relevance confidence scores and search results feed back into the process, allowing the system to automatically adjust and refine its search strategy without requiring manual reconfiguration
Data Source
AI summary
A method and system for carrying out iterative appearance searching is disclosed. The method includes employing at least one first reference image to carry out a first instance, computer vision-driven appearance search of first video data captured across a respective first set of a plurality of first security cameras. The method also includes obtaining a second reference image, having a respective relevance confidence that satisfies a confidence threshold condition, from the portion of the first video data. The method also includes employing the second reference image for a second instance, computer vision-driven appearance search of second video data captured across a respective second set of a plurality of second security cameras.