AI & Machine Learning
Facial Recognition and Video Analytics use Deep Learning technology, which stems from Machine learning (ML), a subset of artificial intelligence (AI).
Facial recognition is the process of identifying or verifying the identity of a person using their face. It captures, analyzes, and compares patterns based on the person’s facial details.
- The face detection process is an essential step in detecting and locating human faces in images and videos.
- The face capture process transforms analogue information (a face) into a set of digital information (data or vectors) based on the person’s facial features.
- The face match process verifies if two faces belong to the same person.
Because facial biometrics is easy to deploy and implement, it continues to be the preferred biometric benchmark. Aside from the absence of physical interaction, face detection and the face match processes are speedy.
Video analytics also referred to as video content analysis or intelligent video analytics, use artificial intelligence to complete various tasks by applying computer vision and deep learning to video footage or live video streams.
There are a large number of applications and use cases in video analytics involving security such as:
- Incident detection
- Intrusion management
- People counting
- Traffic monitoring
- Automatic Number Plate Recognition (ANPR)
- Facial recognition
- Ego-motion estimation.
In addition, video analytics has been useful for industries such as security, retail, healthcare and hospitality, and more.