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SENTIVEILLANCE SERVER
SENTIVEILLANCE SERVER

Sentiveillance server

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PERSONS OR VEHICLES RECOGNITION AND TRACKING FOR VIDEO MANAGEMENT SYSTEMS (VMS)

SentiVeillance Server is a ready-to-use software for easy integration of biometric face identification, vehicle and pedestrian classification and tracking, as well as automatic license plate recognition into operating video management systems (VMS). The software analyzes live video streams, which are served by a VMS from surveillance cameras.

The list of possible uses includes law enforcement, traffic monitoring, security, attendance control, visitor counting and other applications.

 

FEATURES AND CAPABILITIES

  • Ready-to-use facial identification software for surveillance systems.
  • Compatible with major video management systems.
  • Biometric persons identification and tracking.
  • Pedestrians and vehicles tracking and classification.
  • Automated license plate recognition (ALPR) for moving vehicles.
  • Real-time watch list check with automatic event triggering, logging and reporting.
  • Search for events in a timeframe based on person ID, gender or age.
  • Up to 10 video streams from multiple VMS are analyzed in parallel by each SentiVeillance Server.
  • SentiVeillance SDK optionally available for software development.

A video management system (VMS) usually provides only motion detection functionality and can help to filter out parts of video from surveillance cameras when there is no movement. SentiVeillance Server software enhances existing VMS with these features and functions:

  • The ready-to-use SentiVeillance Server software needs only configuration via browser-based interface for connecting an operating VMS.
  • SentiVeillance Server is compatible with Milestone XProtect VMS and Luxriot Evo S and Evo Global video management systems. Each running SentiVeillance Server can connect to multiple VMS and receive more than one video stream from each of them.
  • Biometric persons identification and tracking is based on proprietary facial detection and recognition algorithm, which is based on deep neural networks. The face identification technology is also used in other Neurotechnology products, which have millions of end-user deployments worldwide. The algorithm accuracy and performance has been tested in the NIST Face Recognition Vendor Test (FRVT).
  • Vehicle or pedestrian detection and classification is performed for moving and static objects in the scene. The algorithm can separate these traffic subjects: pedestrians, cars, busses, trucks and bikes. Also, it is possible to estimate color and movement direction for the detected objects.
  • Automated license plate recognition (ALPR) allows to read vehicle's registration numbers after detecting them. The algorithm can process videos from traffic cameras and read license plates from multiple moving vehicles at the same time.
  • SentiVeillance Server analyzes all video streams received from connected VMS in parallel and performs detection and recognition in real-time. All watch list match events trigger alerts, which are sent back to corresponding VMS and reported to an operator, as well as stored in the event log for further reference.
  • Surveillance system operators can perform search in the events log. Search requests are made via VMS user interface and sent to the connected SentiVeillance Server, which returns the search results back. The operator can play back surveillance footage at the timestamps, which are specified by the search results, and perform further actions. The search can be performed within certain timeframe. The search criteria can be one or more person IDs from the watch list, or persons, who belong to specified age or gender group. Finally, operators can review all events with unknown persons.
  • Each SentiVeillance Server can analyze up to 10 video streams in parallel. Several SentiVeillance Servers can connect to the same VMS, as well as several VMS can be connected to the same SentVeillance Server, meaning that SentiVeillance Server software can be integrated into a system with any number of surveillance cameras.