SentiVeillance SDK

Face identification and movement tracking for video surveillance systems

SentiVeillance SDK is designed for developing software that performs biometric face identification and detects moving pedestrians or vehicles or other objects using live video streams from high-resolution digital surveillance cameras.

The SDK is used for passive identification – when passers-by do not make any efforts to be recognized. List of possible uses includes law enforcement, security, attendance control, visitor counting, traffic monitoring and other commercial applications.

Available as a software development kit that allows solution development for Microsoft Windows and Linux platforms.

Download Brochure (PDF).

Download demo application.

Download 30-day SDK Trial.

Technical Specifications

The specifications are provided for the default values of the parameters.

640 x 480 pixels is the recommended minimal frame size for faces' detection. Face template extraction and matching with watchlist database speeds are not dependent on the frame size.

32 pixels is the minimal distance between eyes for a face on video stream or image to perform reliable face tracking and template extraction.

40 x 40 pixels is the minimal moving object size for its detection and tracking.

Face, pedestrians or moving objects tracking performance is dependent on actual size of a face or an object in a frame, not on the size of the whole frame.

SentiVeillance has certain tolerance to face posture that assures face detection and tracking:

  • head roll (tilt) – ±180 degrees (configurable);
    ±15 degrees default value is the fastest setting which is usually sufficient for most near-frontal face images.
  • head pitch (nod) – ±15 degrees from frontal position.
  • head yaw (bobble) – ±45 degrees from frontal position (configurable).
    ±15 degrees default value is the fastest setting which is usually sufficient for most near-frontal face images.

See also the whole list of recommendations and constraints for SentiVeillance usage.

7 kilobytes facial template size assures best accuracy and good performance of the facial recognition algorithm. 4 and 5 kilobytes template sizes are also available.

At least 2 processor cores are required to process surveillance data from one camera with moderate number of faces in a frame. A PC, which has a processor with 4 cores, can be used to process data from 2 cameras almost without performance decrease. If large number of faces in a frame is expected, data processing will require to utilize more processor cores or to use more powerful processor.

The performance specifications are provided for Intel Core i7-4771 processor, running at 3.5 GHz clock rate, and 1920 x 1080 pixels videos.

SentiVeillance 5.0 algorithm technical specifications
Frame rate when tracking up to 5 faces More than 20 frames per second
Frame rate when tracking up to 3 pedestrians More than 30 frames per second
Frame rate when tracking up to 4 cars and occasional pedestrians More than 27 frames per second
Face watch-list database matching time (1) Less than 0.5 second
Maximum face watch-list database size Limited by amount of free RAM

(1) up to 30,000 face records in the database; larger database yelds slower response time. Note that each person may be represented by several records in the database with different appearance variations, different capture angles etc.