Unobtrusive multi-modal biometric recognition using activity-related signatures

  title={Unobtrusive multi-modal biometric recognition using activity-related signatures},
  author={Anastasios Drosou and Georgios Stavropoulos and Dimosthenis Ioannidis and Konstantinos Moustakas and Dimitrios Tzovaras},
  journal={Iet Computer Vision},
The present study proposes a novel multimodal biometrics framework for identity recognition and verification following the concept of the so called ‘on-the-move’ biometry, which sets as the final objective the non-stop authentication in an unobtrusive manner. Gait, that forms the major modality of the scheme, is complemented by new dynamic biometric signatures extracted from several activities performed by the user. Gait recognition is performed through a robust scheme that is based on… 
Activity related authentication using prehension biometrics
Continuous authentication using activity-related traits
Human identification using biometrics has been a major issue in forensics and security applications for many decades. The growing complexity that is introduced by vast databases and advanced spoofing
Activity related biometrics for person authentication
This thesis deals with the investigation of novel, activity-related biometric traits and their potential for multiple and unobtrusive authentication based on the spatiotemporal analysis of human activities, and introduces a new type of biometric, the so-called prehension biometrics, which is introduced and thoroughly studied herein.
New Approach for Multimodal Biometric Recognition
In this work, a novel framework of secured multimodal biometric system is proposed and takes the advantage of proficiency of individual thus overcoming the limitations of a single biometric.
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Front-view Gait Recognition
  • M. Goffredo, J. Carter, M. Nixon
  • Computer Science
    2008 IEEE Second International Conference on Biometrics: Theory, Applications and Systems
  • 2008
A new method for front-view gait biometrics which uses a single non-calibrated camera and extracts unique signatures from descriptors of a silhouette's deformation shows that gait recognition of individuals observed the front can be achieved without any knowledge of camera parameters.
Activity Related Biometrics based on Motion Trajectories
The authentication results performed on a database with 32 subjects show that the current work outperforms existing approaches especially in the case of non-interaction restricting scenarios.
Event-based unobtrusive authentication using multi-view image sequences
Experimental validation illustrates that the proposed approach for integrating static anthropometric features and activity-related recognition advances significantly the authentication performance.
Fusion of static and dynamic body biometrics for gait recognition
A visual recognition algorithm based upon fusion of static and dynamic body biometrics that is effectively fused on decision level using different combination rules to improve the performance of both identification and verification is proposed.
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The obtained results show that human identification by gait can be achieved without any knowledge of internal or external camera parameters with a mean correct classification rate of 73.6% across all views using purely dynamic gait features.
The University of Southampton Multi-Biometric Tunnel and introducing a novel 3D gait dataset
This paper presents the University of Southampton multi-biometric tunnel, a constrained environment that is designed with airports and other high throughput environments in mind. It is able to
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On the Potential of Activity Related Recognition
The authentication potential of the proposed biometric features has been seen to be very high in the performed experiments and the proprietary ACTIBIO-database verify this potential of activity related authentication within the proposed scheme.
Markerless view independent gait analysis with self-camera calibration
The obtained results show that markerless gait analysis can be achieved without any knowledge of internal or external camera parameters and that the obtained data that can be used for gait biometrics purposes.