The Third Dimension

For years, face recognition technology has fought against its poor reputation for inaccuracy and lack of reliability. But a new approach to face recognition — capturing and matching 3D images designed specifically for identity and access management applications — may be the technology that can address the historical concerns. 3D face recognition can be accurate, fast and simple.

Face recognition has been gaining popularity as a biometric identity verification solution, with revenue expected to exceed $1 billion annually by 2012, according to the Biometric Market and Industry Report 2007-2012 from the International Biometric Group (IBG) .

3D face recognition systems are being used by financial institutions, Fortune 500 companies, biopharmaceuticals, casinos and organizations in the transportation sector to enhance security without introducing complex access control procedures that make it difficult for employees to gain entry. In organizations with a large workforce, speedy access control is a must, and with 3D face recognition, companies can quickly authenticate thousands of employees as they begin a shift.

The Advantages of 3D

While two-dimensional (2D) face recognition is being used by law enforcement for identification, it is not significantly deployed for verification systems. Identification involves comparing an existing image against a large image database in order to identify the individual depicted.

In verification solutions, a biometric identifier is compared either to another template called up through a PIN number or smart card, or against a small database of other templates. However, because 2D face recognition systems are affected by lighting conditions and the pose of the individual's face, they are generally not ideal for access control. In U.K. trials for biometric passports, for example, only 69 percent of able-bodied volunteers and 48 percent of disabled participants were correctly authenticated. Some 3D facial recognition systems combat this problem by using their own near-infrared light source, which enables accurate matching even in poor lighting conditions.

3D facial recognition technology also has other advantages. It is possible to collect more data points with 3D, and the types of data points collected are more valuable. While a 2D system might make a match using such data points as the distance between the eyes, 3D uses data such as the curvature of the forehead. The latter is more useful because it allows 3D systems to make matches even if a face changes as a result of a scar or other visual features.

How 3D Works

There are two main approaches to 3D facial recognition: the stereo approach and the structured light approach. Stereo 3D systems create 3D images by synthesizing two or more 2D photos. This computing-intensive (and thus, expensive) approach adds an unnecessary layer of complexity to 3D face matching and, like 2D, is hampered by poor lighting conditions.

Structured light 3D face readers, on the other hand, shine an invisible, near-infrared, grid-shaped light on a user's face and a camera takes a picture of the distortions in the grid caused by the face, collecting approximately 40,000 data points. Because structured light 3D face scanners use their own light source, they can work in poor lighting conditions. They can also accommodate various facial positions, making it easier for users to confirm their identity as they pause in front of the face reader for identity verification.

3D face readers simplify data entry for end-users, who can confirm their identity using only their face. Users just walk up to the reader and pause while the reader either searches the database for a face that matches or checks the face against a template called up by a proximity card, smart card or token — making a match in under a second.