VeriLook improves facial recognition in video-surveillance systems
Neurotechnology announced the availability of VeriLook Surveillance 2.0, a software development kit (SDK) for biometric face identification using live video streams from single or multiple high-resolution digital surveillance cameras.
VeriLook Surveillance 2.0 provides real-time identification of faces and can be used in a wide range of surveillance systems for retail and commercial areas, entrance monitoring and counting, automated time-attendance systems, law enforcement applications and transportation security.
The new, integrated face tracking algorithm in VeriLook Surveillance 2.0 includes a robust, dynamic face model which can adapt to visual appearance changes as subjects move across the scene. It continues tracking of subjects even when their faces briefly disappear from the frame or when they are partially blocked by other objects or even other faces (a common problem while tracking multiple faces). Because it can now simultaneously process video streams from multiple surveillance cameras, VeriLook Surveillance 2.0 is suitable for use in large surveillance systems.
VeriLook Surveillance 2.0 incorporates the VeriLook 5.1 face recognition algorithm, which enables detection of faces with up to 45 degrees out-of-plane rotation in yaw angle. The new face tracking algorithm uses motion prediction models to re-localize faces that have undergone full occlusion, such as when a subject has been fully obstructed by a wall and emerged on the other side. The dynamic face model allows the system to efficiently and reliably track faces in front of complex backgrounds and ensures that subjects can be localized in all video frames, even under strenuous conditions. Face images can then be matched against internal databases, such as criminal watch lists or authorized personnel, and VeriLook Surveillance will immediately report recognized faces to the system.