Browsing by Subject "Biometrics"

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Effects of displacement on identity
(2019-05) Greene, Kimberly Jean; McGlone, Matthew S., 1966-
The concepts of identity and identification are of enormous significance to millions of displaced people worldwide. Among the more than one billion people who lack any official form of identity are refugees, asylum seekers, and displaced people. The United Nations, European Union, and several international state and humanitarian agencies provide aid and protection for those who qualify. Processes of qualification by means of identification and registration are often made difficult by the very circumstances of displacement. Identity and identification are intertwined throughout all phases of the refugee lifecycle, acting upon each other as subject, object, and, at times, both. On a psychological level, migrant identity is affected by several events and experiences, including the identification process itself, during all phases of the journey; resulting changes in identity likely influence participation in the identification process. Ultimately, aid-seeker fate is determined by questions of identity and identification, striking at the very heart of existence: Who am I?
New approaches to automatic 3-D and 2-D 3-D face recognition
(2011-05) Jahanbin, Sina; Bovik, Alan C. (Alan Conrad), 1958-; Castleman, Kenneth; Markey, Mia K.; Vishwanath, Sriram; Grauman, Kristen; Fussell, Donald S.
Automatic face recognition has attracted the attention of many research institutes, commercial industries, and government agencies in the past few years mainly due to the emergence of numerous applications, such as surveillance, access control to secure facilities, and airport screening. Almost all of the research on the early days of face recognition was focused on using 2-D (intensity/portrait) images of the face. While several sophisticated 2-D solutions have been proposed, unbiased evaluation studies show that their collective performance remains unsatisfactory, and degrades significantly with variations in lighting condition, face position, makeup, or existence of non-neutral facial expressions. Recent developments in 3-D imaging technology has made cheaper, quicker and more reliable acquisition of 3-D facial models a reality. These 3-D facial models contain information about the anatomical structure of the face that remains constant under variable lighting conditions, facial makeup, and pose variations. Thus, researchers are considering to utilize 3-D structure of the face alone or in combination with 2-D information to alleviate inherent limitations of 2-D images and attain better performance. Published 3-D face recognition algorithms have demonstrated promising results confirming the effectiveness of 3-D facial models in dealing with the above mentioned factors contributing to the failure of 2-D face recognition systems. However, the majority of these 3-D algorithms are extensions of conventional 2-D approaches, where intensity images are simply replaced by 3-D models rendered as range images. These algorithms are not specifically tailored to exploit abundant geometric and anthropometric clues available in 3-D facial models. In this dissertation we introduce innovative 3-D and 2-D+3-D facial measurements (features) that effectively describe the geometric characteristics of the corresponding faces. Some of the features described in this dissertation, as well as many features proposed in the literature are defined around or between meaningful facial landmarks (fiducial points). In order to reach our goal of designing an accurate automatic face recognition system, we also propose a novel algorithm combining 3-D (range) and 2-D (portrait) Gabor clues to pinpoint a number of points with meaningful anthropometric definitions with significantly better accuracies than those achievable using a single modality alone. This dissertation is organized as follows. In Chapter 1, various biometric modalities are introduced and the advantages of the facial biometrics over other modalities are discussed. The discussion in Chapter 1 is continued with introduction of the face recognition’s modes of operation followed by some current and potential future applications. The problem statement of this dissertation is also included in this chapter. In Chapter 2, an extensive review of the successful 2-D, 3-D, and 2-D+3-D face recognition algorithms are provided. Chapter 3 presents the details of our innovative 3-D and 2-D+3-D face features, as well as our accurate fiducial point detection algorithm. Conclusions and directions for future extensions are presented in Chapter 4.