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Enabling Technology: |
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Facial recognition systems are built on computer programs that analyze images of human faces for the purpose of identifying them. The programs take a facial image, measure characteristics such as the distance between the eyes, the length of the nose, and the angle of the jaw, and create a unique file called a "template." Using templates, the software then compares that image with another image and produces a score that measures how similar the images are to each other. |
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Facial recognition systems are built on computer programs that analyze images of human faces for the purpose of identifying them. The programs take a facial image, measure characteristics such as the Typical sources of images for use in facial recognition include video camera signals and pre-existing photos such as those in driver's license databases. Facial recognition methods may vary, but they generally involve a series of steps that serve to capture, analyze and compare your face to a database of stored images. Here is the basic process that is used to capture and compare images: Detection - When the system is attached to a video surveillance system, the recognition software searches the field of view of a video camera for faces. If there is a face in the view, it is detected within a fraction of a second. A multi-scale algorithm is used to search for faces in low resolution. The system switches to a high-resolution search only after a head-like shape is detected. Alignment - Once a face is detected, the system determines the head's position, size and pose. A face needs to be turned at least 35 degrees toward the camera for the system to register it. Normalization -The image of the head is scaled and rotated so that it can be registered and mapped into an appropriate size and pose. Normalization is performed regardless of the head's location and distance from the camera. Light does not impact the normalization process. Representation -The system translates the facial data into a unique code. This coding process allows for easier comparison of the newly acquired facial data to stored facial data. |
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[Technology & Solutions] [Fingerprint] [Face] [Signature] [Iris] [Voice] [Services] |
translates the characteristics of a face into a unique set of vectors, which is used by both identification and verification applications for face comparisons made in real-time. Identification involves a one-to-many comparison of an individual's face against all faces in a database in order to determine identity; and verification is characterized as a one-to-one match of an individual's face to his or her stored image for the purpose of confirming identity. Face-recognition technology is unique because of its capabilities of both rapid and accurate real-time acquisition as well as its scalability to databases containing millions of faces. It can instantly calculate an individual's face from either live video or a still digital image, and then search a database of millions in only a few seconds in order to find similar or matching images. Changes in physical appearance, and use of aliases complicate the combating of criminals.
distance between the eyes, the length of the nose, and the angle of the jaw, and create a unique file called a "template." Using templates, the software then compares that image with another image and produces a score that measures how similar the images are to each other.