Neurotechnology Releases New SentiVeillance 8.0 SDK for Identification and Analytics Using Live and Video Streams
VILNIUS, Lithuania, Jan. 18, 2021 /PRNewswire/ -- Neurotechnology, a provider of deep-learning-based solutions and high-precision biometric identification and object recognition technologies, today announced the release of the SentiVeillance 8.0 software development kit (SDK). With SentiVeillance SDK, developers can create identification solutions that use live video streams from digital surveillance cameras or video files. The latest version adds face detection and recognition of people who are wearing masks and includes new algorithms that improve license plate detection and recognition speed and accuracy. It also provides new features for vehicle and human (VH) mode, including car make and model estimation, vehicle angle estimation and cloth and gender estimations for pedestrians. It includes a new working mode combination enabling face and VH modes to be used together for fast and accurate identification.
SentiVeillance 8.0 provides identification and analytics from live digital surveillance streams or video files.
"I am very grateful for all the hard work our team put into this latest release that enhances speed and accuracy and provides compelling new ways to use our software," said Vytautas Pranckenas, SentiVeillance product lead for Neurotechnology. "There has never been a more important time for reliable recognition solutions that can adapt to ne conditions, such as people wearing masks."
The new SentiVeillance mode combination (face and VH) allows tracking of the subject even when the face is no longer visible – functionality that is particularly useful in scenarios where tracking a person's position is important.
BIOMETRIC FACIAL RECOGNITION
VEHICLE and HUMAN DETECTION AND MOVEMENT TRACKING (VH)
AUTOMATIC LICENSE PLATE RECOGNITION (ALPR)
The latter two modes (VH and ALPR) can be used together to create larger, more varied solutions. For example, when conventional ALPR is used for road tolls, automatic car washes or paid parking systems, users might try to avoid paying by altering or exchanging license plates. Stolen vehicles might also have their license plates changed. When using multiple analytics in concert, the resulting solution could match and verify plate numbers with other characteristics of the vehicle, such as type and color, through queries of previously stored values or vehicle registration databases.
The new SentiVeillance is designed to run on multi-core processors for fast performance and can process video data from multiple cameras simultaneously using a common PC (current generation i7 CPU with 8 or more cores) and can utilize multiple graphics processing units (GPUs) to achieve even better performance. It can be used with large surveillance systems, incorporating many cameras and data-processing nodes. Developers have many and varied options in the creation of scalable, cost-effective solutions for their customers.
THERMAL FACES SAMPLE
Jennifer Allen Newton
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