Recent Advances in Behavioural and Cognitive Biometric Recognition
A special issue of Journal of Imaging (ISSN 2313-433X).
Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 243
Special Issue Editor
Special Issue Information
Dear Colleagues,
Biometric recognition has been traditionally described as the exploitation of people’s physical or behavioural characteristics for the design of automatic systems able to identify or authenticate a subject. Even though most commercially-deployed biometric recognition systems rely on physical traits such as fingerprints, the face, and iris, behavioural identifiers offer several advantages which are extremely important for specific applications. For instance, the way people walk and perform gestures can be used to recognise people while keeping sensors at a distance from the interested subjects. The way individuals interact with tools of daily use such as a mouse, a keyboard, or a mobile device could be also employed to discriminate between subjects, without requiring the usage of dedicated hardware. Furthermore, continuous authentication can be achieved through behavioural traits, providing assurance of an individual’s identity over time. Similar properties are also shared by cognitive biometric characteristics, which involve the acquisition of biosignals generated by the nervous system while performing a specific task or in response to a given stimulus, and have recently attracted the attention of the scientific community thanks to their intrinsic liveness detection capability and their robustness against spoofing attacks. Examples of such traits comprise electrocardiography (ECG), blood pulse volume (BVP), electrodermal response (EDR), or electroencephalography (EEG).
The aim of this Special Issue is to present and highlight novel algorithms, architectures, techniques, feature extraction methods, and applications of behavioural and cognitive characteristics for biometric recognition.
Dr. Emanuele Maiorana
Guest Editor
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Keywords
- Cognitive biometrics
- Behavioural biometrics
- Deep learning
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