EN- VMS Crash Course presentations

Facial recognition: things to consider • Hardware requirements & cost • Accepted error margin • Environment Variables

• Video management crash course
• Before we start
• Automation & intelligence
• A new reality
• Slide Number 5
• Expected growth of video surveillance traffic between 2017 and 2022
• Average attention span for concentration oriented tasks
• Slide Number 8
• From unstructured to structured data
• From data to actionable information
• How the market evolved in the last few years
• Why it works today
• Beyond video data
• Metadata explained
• Metadata types in a VMS
• Analytics architectures
• Architecture types
• Edge-based video analytics
• Server-based video analytics
• Server-based video analytics (1)
• Edge-based vs. server-based
• Enhance your video surveillance
• Analytics output
• Video analytics categories
• Slide Number 25
• Perform smart investigations
• Cut down on investigation time
• Slide Number 28
• Pro-actively detect threats
• Protect your perimeter
• Detecting intruders in low light situations
• Detect objects left behind or removed
• Facial recognition
• Identify people
• Facial recognition: things to consider
• Variables
• Slide Number 37
• Slide Number 38
• Improve your operations
• Gather insights and understand your environment
• Monitor the flow of people and vehicles
• Automate camera maintenance
• Slide Number 43
• View video analytics data on visual reports and live dashboards
• Real-life deployments
• Retail
• Buildings & industrial
• Airport
• Power & utilities
• Beyond automation
• Slide Number 51
• Machine learning
• Machine learning (1)
• Improving video analytics
• Machine learning for image recognition
• Deep learning for image recognition
• How those technologies improve security systems
• Results in numbers: people counting
• A look into the future
• Moving towards predictive information
• Wrap-up
• Up next: Module 5
• Slide Number 66