Webcam video surveillance software
Two algorithms for surveillance systems. Depending on the surveillance system design,
one of these algorithms may be used:
- Biometric face recognition algorithm is based on deep neural networks
and provides these capabilities for surveillance systems:
- Multiple face detection, features extraction and template matching
with the internal database in real time.
Facial identification reliability enables using large watchlist databases.
Face tracking is performed in all successive frames from the video source until they disappear
from camera field of view.
The face tracking algorithm uses dynamic face and motion prediction models that make it robust
to occlusions like other objects or even other faces.
The algorithm is able to continue tracking a face even when it re-appears after being fully
covered by occlusions (like walls, furniture, posters etc).
Smile, open-mouth, closed-eyes, glasses, dark-glasses, beard and mustache attributes detection (configurable).
Motion detection and tracking algorithm performs advanced detection of moving objects in the scene,
their classification and tracking until they disappear.
These features are available for surveillance systems:
Object classification. After calibration software allows to perform object classification
based on the size and movement speed.
For example, users can configure a surveillance system to determine if a tracked object is a vehicle,
a single pedestrian or group of pedestrians.
Restricted areas control. Web Camera Pro algorithm can detect and report if people
or objects enter, leave or stay in restricted areas.
The events are triggered when people or objects cross pre-defined lines or enter polygon-shaped areas.
Tolerance to weather conditions. The algorithm ignores rain and snow, as well as trees and bushes,
which are swayed by wind.