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Soft Biometries

Sujet proposé par
Directeur de thèse:
Doctorant: Valeria CHIESA
Unité de recherche UMR 7102 Laboratoire de recherche d'EURECOM

Domaine: Sciences et technologies de l'information et de la communication

Projet

Classical biometry offers a natural and reliable solution for establishing the identity of an individual. The use of human physical and behavioral characteristics has been increasingly adopted in security applications due to various advantages, such as universality, robustness, permanence and accessibility. Currently state–of–the–art intrusion detection and security mechanism systems include meanwhile by default at least one biometric trait. The latest addition of soft biometry inherits a main part of the advantages of classical biometry and furthermore endorses by its own assets. The beginnings of soft biometrics science were laid by Alphonse Bertillon in the 19th century, who firstly introduced the idea for a personal identification system based on biometric, morphological and anthropometric determinations. He used traits like colors of eye, hair, beard and skin; shape and size of the head; general discriminators like height or weight and also description of indelible marks such as birth marks, scars or tattoos. A great majority of those descriptors fall at the present time into the category of soft biometrics. Jain et al. first introduced the term soft biometrics to be a set of characteristics that provide some information about the individual, but are not able to individually authenticate the person, mainly due to the lack of distinctiveness and permanence. Later on, it was also noted that soft biometrics are not expensive to compute, can be sensed at a distance, do not require the cooperation of the surveillance subjects and have the aim to narrow down the search from a group of candidate individuals. Moreover we here note that the human compliance of soft biometrics is a main factor, which differentiates soft biometrics from classical biometrics offering new application fields. Nowadays it is possible to define the soft biometric traits as physical, behavioral or adhered human characteristics, classifiable in pre–defined human compliant categories. These categories are, unlike in the classical biometric case, established and time–proven by humans with the aim of differentiating individuals. In other words the soft biometric traits instances are created in a natural way, used by humans to distinguish their peers. We note that the human compliant labeling is sometimes also referred to as semantic annotation.

Classical biometry offers a natural and reliable solution for establishing the identity of an individual. The use of human physical and behavioral characteristics has been increasingly adopted in security applications due to various advantages, such as universality, robustness, permanence and accessibility. Currently state–of–the–art intrusion detection and security mechanism systems include meanwhile by default at least one biometric trait. The latest addition of soft biometry inherits a main part of the advantages of classical biometry and furthermore endorses by its own assets. The beginnings of soft biometrics science were laid by Alphonse Bertillon in the 19th century, who firstly introduced the idea for a personal identification system based on biometric, morphological and anthropometric determinations. He used traits like colors of eye, hair, beard and skin; shape and size of the head; general discriminators like height or weight and also description of indelible marks such as birth marks, scars or tattoos. A great majority of those descriptors fall at the present time into the category of soft biometrics. Jain et al. first introduced the term soft biometrics to be a set of characteristics that provide some information about the individual, but are not able to individually authenticate the person, mainly due to the lack of distinctiveness and permanence. Later on, it was also noted that soft biometrics are not expensive to compute, can be sensed at a distance, do not require the cooperation of the surveillance subjects and have the aim to narrow down the search from a group of candidate individuals. Moreover we here note that the human compliance of soft biometrics is a main factor, which differentiates soft biometrics from classical biometrics offering new application fields. Nowadays it is possible to define the soft biometric traits as physical, behavioral or adhered human characteristics, classifiable in pre–defined human compliant categories. These categories are, unlike in the classical biometric case, established and time–proven by humans with the aim of differentiating individuals. In other words the soft biometric traits instances are created in a natural way, used by humans to distinguish their peers. We note that the human compliant labeling is sometimes also referred to as semantic annotation.

Enjeux

Second year Within the context of IDEA4SWIFT, the work will consist in detecting possible spoofing attacks and counter-measures The main objective is to make the distinction between a real face and a photography displayed in front of a video camera. The benefits of using new sensors (e.g. plenoptic camera) in this field have already been proved in (Sooyeon Kim, 2014) and (R. Raghavendra, 2015). A deeper study of light field images can improve an anti-spoofing method. The second year may include a visiting stay in one of the extra European partners of the Marie Curie Mobility Project IDENTITY. Third year The content of the third year will be described in one year.