For security professionals and Smart Home users. Quickly scan people present in the scene to shortlist, target and identify potential miscreants.
IntelliVision’s Face Recognizer™ product is a highly accurate, deep learning-based facial recognition solution that uses a stored database of faces to detect, recognize and record people’s faces that appear in a camera’s field of view.
Face Recognizer’s detection capability searches an existing database of faces and compares them with the faces detected in the scene to find a match. Face Recognizer records faces from the camera and detects “people of interest,” providing real-time alerts upon detecting certain faces in the scene.
For security professionals and Smart Home users. Quickly scan people present in the scene to shortlist, target and identify potential miscreants.
Identify and capture human faces from still images, live video and pre-recorded video clips.
Improve security at government, commercial and industrial sites. Improve customer service and security at banks, casinos, retail stores, hotels and restaurants.
Using a combination of AI and Deep Learning, Face Recognizer has achieved accuracy benchmarks comparable to industry leaders like Google and Facebook. It scores the following accuracy in the leading public test databases – LFW: 99.6%, YouTube Faces: 96.5%, MegaFace (with 1000 people/distracters): 95.6%.
Facial Recognition accuracy as high as 99.6% on public standard data set.
Recognition is possible in both real time and offline modes.
Recognition and detection is possible both in real time and off line and recognition and enrollment are available from both video and still images. Recognition in video mode is achieved by analyzing multiple images per face and in video mode recognition is achieved in less than 1-2 seconds.
Face Recognizer is available with a Rest API/SDK for partners and external systems. Easy integration of alerts is achieved through http/JSON and an open architecture.
For partners and external systems.
Windows, Linux, inside camera, cloud solution and embedded systems.
Runs on Windows or Linux for server-based deployment, 1-16 cameras per PC based on CPU capacity. In-camera/embedded, Face Recognizer works with various camera platforms and popular chip sets running Linux. On-cloud it is available as a Web/Server Application and through Cloud Web Services API Interface.
Enable security professionals to shortlist, target and identify intruders, loiterers and potential miscreants
Automatically create a log of people in the camera or scene which can be used for forensic investigations
Enable automated matching against a watch list with real time alerting