Face Recognition

AI-DRIVEN SECURITY

Our software makes video surveillance smart, changing cameras from just seeing to thinking – object detections, face recognitions, car plate recognitions and real-time video content analysis.


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Face recognition in video surveillance
Facial recognition is a way of recognizing a human face through technology. A facial recognition system uses biometrics to map facial features from a photograph or video. It compares the information with a database of known faces to find a match. Facial recognition can help verify personal identity, but it also raises privacy issues.

The most common example of computer vision in facial recognition is for securing smartphones. More advanced uses of facial recognition and biometrics include in residential or business security systems that use unique physiological features of individuals to verify their identity. Deep learning algorithms can identify the unique patterns in a person's fingerprints and use it to control access to high-security areas such as high-confidentiality workplaces, such as nuclear powerplants, research labs, and bank vaults.

Computer vision, or the ability of artificially intelligent systems to "see" like humans, has been a subject of increasing interest and rigorous research now. As a way of emulating the human visual system, the research in the field of computer vision purports to develop machines that can automate tasks that require visual cognition. However, the process of deciphering images, due to the significantly greater amount of multi-dimensional data that needs analysis, is much more complex than understanding other forms of binary information. This makes developing AI systems that can recognize visual data more complicated.
But, the use artificial neural networks is making computer vision more capable of replicating human vision. Computer vision technology of today is powered by deep learning algorithms that use a special kind of neural networks, called convolutional neural network (CNN), to make sense of images.

Web Camera Pro application uses data vision theory to identify objects within video, search through catalogues of images, and extract information out of images. Computer vision provides the functions for recognizing and identifying an image as a specific object.

Object detection deals with detecting instances of semantic objects of a certain class (such as a dog, a human, or a car.) in digital images and videos.

Web Camera Pro - video surveillance with artificial intelligence.