Face Recognition (FRS) for VIP Security: Identifying Suspects and Criminals

Industry

Surveillance Security

Duration

3 months

Team Size

4 people

Project Overview

This case study shows how our Face Recognition System (FRS) helps security teams identify persons of interest—including suspects, known criminals, and high-risk individuals—in real time at critical entry points.
The solution is built to work with a large watchlist database containing thousands of criminal and blacklist profiles, and it also supports suspicious/unusual behaviour detection to flag potential risks even when the person’s identity is unknown. When a match or risky behaviour is detected, the system triggers an immediate alert with evidence, enabling faster verification and response while maintaining controlled access to sensitive watchlist data.

Client Struggle

Before this solution, screening depended on manual observation and delayed coordination. Even with CCTV coverage, teams often reacted only after an incident or after reviewing footage later.
A person of interest could cross an entry point before anyone realized the risk. Alerts were not standardized, evidence was scattered across cameras, and escalation relied on calls and human judgement under pressure. In short, security operations were reactive, inconsistent, and difficult to scale across multiple entrances.

What They Wanted

1
Automatically identify suspects, criminals, and persons of interest using FRS
2
Support a large-scale watchlist (thousands of profiles) with reliable matching
3
Trigger instant alerts when a watchlist match occurs
4
Provide evidence snapshots, match score/confidence, and camera/location context
5
Detect and alert on unusual/suspicious behaviour (even if identity is not known)
6
Enable a clear verify → escalate → close workflow for faster response
7
Maintain controlled access and separation between sensitive watchlist data and daily monitoring
8
Scale easily across multiple cameras, entrances, and sites

What We Built

We implemented an FRS-driven security recognition platform with a dual-portal architecture designed for strict access control and smooth operations.

1) Watchlist Admin Portal (Highly Restricted)

A secure portal for authorized users to manage watchlist profiles:

1
Enroll and manage criminal/suspects/POI profiles
2
Store face images and key metadata (name/alias, category, risk level, reference ID, notes)
3
Enable/disable profiles instantly as cases change
4
Role-based access so only approved personnel can view or modify watchlist data

2) Security Operations Portal (SOC / Control Room)

An operations dashboard for live monitoring and alert handling:

1
Real-time alerts with camera name, location, time, and evidence snapshot(s)
2
Alert status workflow: New → Under Review → Verified → Escalated → Closed
3
Search and filter by entrance, time, category, risk level, or status
4
Evidence review panel to support rapid verification and decision making

3) Real-Time Smart Alerting (Identity + Behaviour)

1
Identity Matching Alerts: When FRS matches a face against the watchlist, the system triggers a high-priority alert instantly
2
Behaviour-Based Risk Alerts: When a person is not identified but shows unusual/suspicious behaviour, the system triggers a separate behaviour alert for investigation

This ensures security teams get early warning even when identity is unknown.

How It Works

Step 1: Watchlist Enrollment (Admin Portal)

1
The authorized security admin adds a person-of-interest profile with face images and relevant details, then activates the profile so it becomes searchable in real-time recognition.

Step 2: Live Monitoring (SOC Portal)

1
SOC operators monitor entrances through the dashboard. Cameras run continuous face detection and recognition.

Step 3: Detection + Decision Layer (FRS + Behaviour Analytics))

When a person enters:

1
Camera captures the face at the entry point
2
FRS compares the face against the thousands-profile watchlist
3
If a match occurs → Watchlist Alert (High Priority) appears instantly
4
If no match but behaviour looks unusual → Suspicious Behaviour Alert (Review Required) appears

Step 4: Alert Verification & Escalation

1
Operator reviews evidence snapshot(s) and match details
2
If verified, operator escalates to the response team with location and context
3
Optional integrations (based on site policy): access control action, siren/hooter trigger, message notifications to responders
4
All actions are tracked within the alert workflow for operational clarity

Why This Approach Worked

This approach replaced manual dependency with real-time intelligence. Watchlist matching ensured known threats were detected instantly, while suspicious behaviour detection provided coverage for unknown risks.

The two-portal structure kept operations clean and secure:

1
1. Watchlist data stayed protected with restricted access
2
2. SOC teams focused on monitoring and action without accessing sensitive admin functions
3
3. Workflows became standardized across shifts and entrances

The system is also scalable—additional cameras, entry points, and sites can be added without changing the core process.

Results

After implementation:

1
Watchlist matches were detected immediately, reducing response time
2
Security teams gained centralized visibility across entrances and zones
3
Verification became faster and more structured with clear alert workflows
4
Unidentified but risky individuals were still flagged via unusual behaviour alerts
5
Security operations became more proactive, consistent, and professional

Conclusion

This solution combines Face Recognition (FRS) with secure watchlist operations and suspicious behaviour detection to strengthen entry-point security. It is designed to scale across multiple entrances and cameras while keeping sensitive data protected and enabling fast, evidence-backed decision making.

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