Multimodal User Interfaces: Who’s the User?

Anil K. Jain

Department of Computer Science & Engineering, Michigan State University

 A wide variety of systems require reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that only a legitimate user, and not anyone else, accesses the rendered services. Examples of such applications include secure access to buildings, computer systems, laptops, cellular phones and ATMs. Biometric recognition, or simply biometrics, refers to the automatic recognition of individuals based on their physiological and/or behavioral characteristics. By using biometrics it is possible to confirm or establish an individual’s identity based on “who she is”, rather than by “what she possesses” (e.g., an ID card) or “what she remembers” (e.g., a password). Current biometric systems make use of fingerprints, hand geometry, iris, face, voice, etc. to establish a person's identity. Biometric systems also introduce an aspect of user convenience. For example, they alleviate the need for a user to “remember” multiple passwords associated with different applications. A biometric system that uses a single biometric trait for recognition has to contend with problems related to non-universality of the trait, spoof attacks, limited degrees of freedom, large intra-class variability, and noisy data. Some of these problems can be addressed by integrating the evidence presented by multiple biometric traits of a user (e.g., face and iris). Such systems, known as multimodal biometric systems, demonstrate substantial improvement in recognition performance. In this talk, we will present various applications of biometrics, challenges associated in designing biometric systems, and various fusion strategies available to implement a multimodal biometric system.


    Anil Jain is a University Distinguished Professor in the Department of Computer Science and Engineering at Michigan State University. His research interests include statistical pattern recognition, computer vision, and biometric authentication.  He received the Pattern Recognition Society's best paper awards in 1987 and 1991 and received the 1996 IEEE Trans. Neural Networks Outstanding Paper Award. He has served as the Editor-in-Chief of the IEEE Trans. on Pattern Analysis and Machine Intelligence. He has written and edited a number of books, including BIOMETRICS: Personal Identification in Networked Society, Kluwer (1999) and Handbook of Fingerprint Recognition, Springer (2003). He holds six patents in the area of fingerprint recognition. He is a Fellow of the IEEE and IAPR. He has received a Fulbright Research award, Alexander Von Humboldt Research award, and was named a Fellow of the John Simon Guggenheim Memorial Foundation. He delivered the 2002 Pierre Devijver Lecture sponsored by the International Association of Pattern Recognition.