ACS

ACS presents SAVAS – Situational Awareness Video Analytics System.

SAVAS is a video object analysis system that observes a specific area cell or scene and studies the behavior of the various moving objects within that area cell or scene. The system establishes the behavior patterns of the various moving objects and determines the dynamic visual routine of the area cell.

Based on these reference definitions, the system can then detect and identify any deviations from the standard behavior patterns and the established visual routine.

SAVAS assembles a 3D situational awareness picture of densely-populated urban area cells & scenes, then automatically detects & identifies any deviations from the established visual routine within the area cells or scenes being monitored and alerts the user of such irregularities.

In response to the alert generated by the system, the user can review the video footage covering the cause of the alert in real-time or retrospectively.

SAVAS eliminates the need for continuous monitoring of multiple visual displays by numerous human operators and reduces the over-all number of displays being monitored as well as the number of displays monitored by each operator.

Resolving such visual surveillance challenges as occlusions, shadows and high density scenes, SAVAS provides an accurate estimate of the objects’ spatial positions, velocity & heading data.

SAVAS features extensive video input recording & storage capabilities, thereby enabling After-Action Review (AAR) & analysis.

SAVAS offers a cutting-edge video analytics solution that significantly improves the efficiency of visual surveillance in such applications as border checkpoints, sensitive installations, transportation terminals, shopping malls & commercial centers, cultural centers & crowded public areas and mass-audience events.

Key Features & Advantages

• Cutting-edge video analytics system studies the dynamic visual routine of a given area cell or scene and assembles a 3D situational awareness picture of that area cell or scene
• Reference definitions enable automatic detection of visual irregularities & generation of alerts
• Automated process eliminates the need for continuous monitoring of multiple displays by numerous human operators
• The number of displays being monitored is significantly reduced
• Occlusions, shadows & high density scenes processed & resolved
• Accurate estimate of objects’ spatial positions, velocity & heading
• Recording & storage of video input for After-Action Review (AAR) & analysis
• Typical applications:
  • Border checkpoints
  • Sensitive installations
  • Transportation terminals
  • Shopping malls & commercial centers
  • Cultural centers & other crowded public areas
  • Mass-audience events