Surveillance System Appearance Search Using Access Control Reference Images
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Solution Overview
Problem
Current surveillance systems rely heavily on human operators for object detection and classification, and access control systems lack efficient methods to verify authorized individuals automatically, especially in real-time and computationally efficient manners.
Innovation Solution
A method and system that involves receiving user input to match a name with a registered individual in an access control database, populating user interface pages with images of the individual, and allowing user selection to mark images as reference for an appearance search within a surveillance system, enabling automatic identification and classification of individuals across video recordings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If human operators perform object detection and classification in surveillance systems, then identification accuracy can be maintained, but operational efficiency and productivity are reduced due to manual labor requirements
Solution Approach 1:
The surveillance system performs automatic object detection, classification, and identification without requiring human operators to manually analyze video feeds. The system uses AI algorithms to independently detect objects, classify them into categories, and identify individuals by matching facial features against databases, thereby eliminating manual labor and significantly improving operational efficiency
Solution Approach 2:
The patent replaces the mechanical process of human visual inspection and manual object identification with automated electronic systems. Computer vision algorithms and machine learning models substitute for human operators, enabling the system to process video data, detect objects, and identify individuals through computational methods rather than manual observation
2Speed
If access control systems verify authorized individuals manually, then security reliability can be maintained, but verification speed and real-time capability are reduced
Solution Approach 1:
The system pre-processes and stores facial feature data of authorized individuals in databases before access verification is needed. When someone attempts to access a secured area, the system quickly compares their facial features against the pre-stored data, enabling rapid verification without manual intervention while maintaining high security reliability through accurate biometric matching
Solution Approach 2:
The patent replaces manual identity verification processes with automated biometric authentication systems. Facial recognition technology and other biometric sensors substitute for manual ID checking, enabling the system to verify authorized individuals rapidly through electronic comparison of biometric data against stored profiles, thereby increasing verification speed while maintaining security reliability
3Productivity
If surveillance systems process and analyze video data automatically, then productivity and real-time capability are improved, but computational complexity and system complexity increase
Solution Approach 1:
The patent divides the complex video analysis process into distinct modular components: object detection modules that identify potential objects in video frames, classification modules that categorize detected objects into types, and identification modules that match facial features against databases. This segmentation allows each component to specialize in specific tasks, improving real-time processing capability while managing system complexity through modular architecture
Solution Approach 2:
The system employs multi-functional AI algorithms that can perform multiple tasks using the same computational framework. The object detection models can simultaneously detect various types of objects (people, vehicles, animals), classify them into categories, and extract facial features for identification all within a unified processing pipeline, thereby improving productivity without proportionally increasing system complexity
4Measurement precision
If access control systems store and manage detailed individual information, then identification accuracy is improved, but data management complexity and privacy concerns increase
Solution Approach 1:
The system extracts and stores only the essential biometric features needed for identification, such as facial feature points and geometric relationships, rather than storing complete images or personal information. This extraction approach maintains high identification accuracy by preserving distinctive biometric characteristics while reducing data management complexity and minimizing privacy concerns through selective data retention
Data Source
AI summary
Methods, systems, and techniques for enhancing a VMS are disclosed. One of the disclosed methods includes populating a user interface page with one or more images, each showing a single person matched to a known identity, and each taken contemporaneously with one or more respective access control event occurrences identifiable to the single person. User selection input is receivable to mark at least one of the images as a reference image for an appearance search to find additional images of the single person captured by video cameras within a surveillance system.