These databases often include biographical information such as name, age, SSN, and more. Commercial deployments of face recognition systems, such as systems you may see in airports around the world, generally reference a database of faces. Given an image or a video of a face, Face Attributes extracts information such as gender, ethnicity, emotions, age, facial landmarks, etc.ĭata, in the case of face recognition, is a set of quantitative or qualitative values for reference. Some photo storage applications use Face Matching to tag a face that appears in various photos, and many smartphones use the technology to unlock your phone. This is where algorithms meet databases for face search and retention. Given a target face and a set of candidate faces, Face Matching finds which one of the candidate faces belongs to the target face. For example, if your face appears in the beginning of a video, and again at the end, Face Re-identification can recognize that it's the same face without identifying your face by comparing it to a database of faces. Note: tracking specific facial features (such as eyebrows, lips, etc.) is another area of research.įace Re-identification is conceptually similar to Face Tracking, except the corresponding frames are not necessarily consecutive in the video. This is useful for a police agency when they need to blur out an individual's face in a body-worn video that they want to release to the public. 1 shows the face of one person being matched between two frames. In a given video, Face Tracking corresponds a face from one frame to the next consecutive frame. Most commodity digital cameras, including mobile phones, run Face Detection to enhance image quality.

1 highlights the detected faces in dotted boxes. In a given image, Face Detection finds faces and their locations.

Axon face2face