Camera-Based Social Network Discovery System
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Solution Overview
Problem
Current video-based site surveillance systems are inefficient in identifying social networks and cohesive groups in real-time, relying on manual observation or post-event analysis, which hinders predictive security efforts.
Innovation Solution
A computer-implemented method and system that utilizes face capture and tracking cameras to automatically associate individuals with unique identifiers and track their interactions, employing graph-cut and modularity-cut algorithms to construct social networks and identify leadership structures within these networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual observation or post-event video analysis is used to identify social networks, then personnel can observe social relationships, but the process is time-consuming and highly inefficient
Solution Approach 1:
The patent replaces manual mechanical observation by security personnel with an automated computer vision system that uses machine learning algorithms to detect faces, recognize individuals, track movements, and analyze social interactions automatically, thereby dramatically improving efficiency and eliminating time-consuming manual processes
Solution Approach 2:
The system enables self-service by allowing the surveillance system to automatically perform social network analysis without human intervention. The computer vision system autonomously captures images, identifies individuals, tracks their interactions, and generates social network maps, freeing personnel from manual observation tasks
2Measurement precision
If facial recognition is implemented in camera systems, then individual identification is improved, but the system complexity increases
Solution Approach 1:
The patent segments the complex surveillance system into distinct functional modules: face detection module, face recognition module, tracking module, and social network analysis module. Each module performs a specific task, making the overall system more manageable and maintainable while achieving high identification accuracy
Solution Approach 2:
The system introduces intermediate processing stages including face feature extraction and matching algorithms that serve as mediators between image capture and individual identification. These intermediaries break down the complex recognition process into manageable steps, reducing overall system complexity
Data Source
AI summary
A system, method and program product for camera-based discovery of social networks. The computer implemented method for identifying individuals and associating tracks with individuals in camera-generated images from a face capture camera(s) and a tracking camera(s), wherein the computer implemented method includes: receiving images of an individual from the face capture camera(s) on a computer; receiving images of a track(s) of an individual from the tracking camera(s) on a computer; automatically determining with the computer the track(s) from the images from the tracking camera(s); and associating with the computer the track(s) with the individual(s) and a unique identifier. The present invention has been described in terms of specific embodiment(s), and it is recognized that equivalents, alternatives, and modifications, aside from those expressly stated, are possible and within the scope of the appending claims.