EN- VMS Crash Course presentations

Detect objects left behind or removed Notify operators of dangerous objects in certain areas, or when something was removed. Can also be used to detect stopped cars or trains.

• 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