Using Ocular Data for Unconstrained Biometric Recognition

Using Ocular Data for Unconstrained Biometric Recognition

Hugo Proença (University of Beira Interior, Portugal), Gil Santos (University of Beira Interior, Portugal) and João C. Neves (University of Beira Interior, Portugal)
Copyright: © 2014 |Pages: 20
DOI: 10.4018/978-1-4666-5966-7.ch012
OnDemand PDF Download:
$30.00
List Price: $37.50

Abstract

There are several scenarios where a full facial picture cannot be obtained nor the iris properly imaged. For such cases, a good possibility might be to use the ocular region for recognition, which is a relatively new idea and is regarded as a good trade-off between using the whole face or the iris alone. The area in the vicinity of the eyes is designated as periocular and is particularly useful on less constrained conditions, when image acquisition is unreliable, or to avoid iris pattern spoofing. This chapter provides a comprehensive summary of the most relevant research conducted in the scope of ocular (periocular) recognition methods. The authors compare the main features of the publicly available data sets and summarize the techniques most frequently used in the recognition algorithms in this chapter. In addition, they present the state-of-the-art results in terms of recognition accuracy and discuss the current issues on this topic, together with some directions for further work.
Chapter Preview
Top

2. Periocular Anatomy And Strctures

Not only the superficial features of the skin determine the facial appearance, but also the concavities and convexities conferred by the underlying bones and muscles play a significant role. In particular, the periocular region comprises many anatomic features and landmarks that potentially fit for recognition purposes (Figure 1).

Figure 1.

Anatomic features on the periocular region

Complete Chapter List

Search this Book:
Reset