The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Articulated Soft Objects for Multiview Shape and Motion Capture
IEEE Transactions on Pattern Analysis and Machine Intelligence
Considering Reach in Tangible and Table Top Design
TABLETOP '06 Proceedings of the First IEEE International Workshop on Horizontal Interactive Human-Computer Systems
Tracking of the Articulated Upper Body on Multi-View Stereo Image Sequences
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
HHMM Based Recognition of Human Activity*This paper was presented at MVA2005.
IEICE - Transactions on Information and Systems
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Video understanding for complex activity recognition
Machine Vision and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Circuits and Systems for Video Technology
A hybrid discriminative/generative approach for modeling human activities
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Assessing the uniqueness and permanence of facial actions for use in biometric applications
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on recent advances in biometrics
Performance analysis for automated gait extraction and recognition in multi-camera surveillance
Multimedia Tools and Applications
View-invariant gesture recognition using 3D optical flow and harmonic motion context
Computer Vision and Image Understanding
Skeleton and shape adjustment and tracking in multicamera environments
AMDO'10 Proceedings of the 6th international conference on Articulated motion and deformable objects
Event-based unobtrusive authentication using multi-view image sequences
Proceedings of the first ACM international workshop on Analysis and retrieval of tracked events and motion in imagery streams
View-Independent Action Recognition from Temporal Self-Similarities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-time upper body detection and 3d pose estimation in monoscopic images
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Application of Projective Invariants in Hand Geometry Biometrics
IEEE Transactions on Information Forensics and Security
Performance analysis of iris-based identification system at the matching score level
IEEE Transactions on Information Forensics and Security
IEEE Transactions on Multimedia
Identification of humans using gait
IEEE Transactions on Image Processing
Learning and Matching of Dynamic Shape Manifolds for Human Action Recognition
IEEE Transactions on Image Processing
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
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This paper presents a novel framework for unobtrusive biometric authentication based on the spatiotemporal analysis of human activities. Initially, the subject's actions that are recorded by a stereoscopic camera, are detected utilizing motion history images. Then, two novel unobtrusive biometric traits are proposed, namely the static anthropometric profile that accurately encodes the inter-subject variability with respect to human body dimensions, while the activity related trait that is based on dynamic motion trajectories encodes the behavioral inter-subject variability for performing a specific action. Subsequently, score level fusion is performed via support vector machines. Finally, an ergonomics-based quality indicator is introduced for the evaluation of the authentication potential for a specific trial. Experimental validation on data from two different datasets, illustrates the significant biometric authentication potential of the proposed framework in realistic scenarios, whereby the user is unobtrusively observed, while the use of the static anthropometric profile is seen to significantly improve performance with respect to state-of-the-art approaches.