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Proceedings ArticleDOI

A Leap Password based verification system

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TLDR
This research proposes Leap Password; a novel approach for biometric authentication that consists of a string of successive gestures performed by the user during which physiological as well as behavioral information is captured.
Abstract
Recent developments in three-dimensional sensing devices has led to the proposal of a number of biometric modalities for non-critical scenarios. Leap Motion device has received attention from Vision and Biometrics community due to its high precision tracking. In this research, we propose Leap Password; a novel approach for biometric authentication. The Leap Password consists of a string of successive gestures performed by the user during which physiological as well as behavioral information is captured. The Conditional Mutual Information Maximization algorithm selects the optimal feature set from the extracted information. Match-score fusion is performed to reconcile information from multiple classifiers. Experiments are performed on the Leap Password Dataset, which consists of over 1700 samples obtained from 150 subjects. An accuracy of over 81% is achieved, which shows the effectiveness of the proposed approach.

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Citations
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Journal ArticleDOI

Review of Three-Dimensional Human-Computer Interaction with Focus on the Leap Motion Controller

TL;DR: The purpose of this paper is to survey the state-of-the-art Human-Computer Interaction techniques with a focus on the special field of three-dimensional interaction, including an overview of currently available interaction devices, their applications of usage and underlying methods for gesture design and recognition.
Journal ArticleDOI

Hand Tremor Based Biometric Recognition Using Leap Motion Device

TL;DR: It is considered that the proposed approach has the potential to be used as a new biometric identification manner in the field of security.
Proceedings ArticleDOI

A data driven in-air-handwriting biometric authentication system

TL;DR: A new finger-gesture-based authentication method, where the in-air-handwriting of each user is captured by wearable inertial sensors, which delivers a significant performance improvement compared to the existing gesture-based biometric authentication systems.
Proceedings ArticleDOI

Multifactor User Authentication with In-Air-Handwriting and Hand Geometry

TL;DR: This paper proposes a multifactor user authentication framework using both the motion signal of a piece of in-air-handwriting and the geometry of hand skeleton captured by a depth camera and presents an in-depth analysis of the utilized features to explain the reason for the performance boost.
Journal ArticleDOI

Analysis of 3D signatures recorded using leap motion sensor

TL;DR: It is shown that the 3rd dimension, which essentially represents instantaneous pressure during writing, can improve the accuracy of the biometric systems and believe, Leap motion can be an alternative to the existing biometric setups.
References
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Journal ArticleDOI

An introduction to variable and feature selection

TL;DR: The contributions of this special issue cover a wide range of aspects of variable selection: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.
Journal ArticleDOI

Note on the sampling error of the difference between correlated proportions or percentages.

TL;DR: Two formulas are presented for judging the significance of the difference between correlated proportions and the chi square equivalent of one of the developed formulas.
Journal ArticleDOI

Microsoft Kinect Sensor and Its Effect

TL;DR: While the Kinect sensor incorporates several advanced sensing hardware, this article focuses on the vision aspect of the sensor and its impact beyond the gaming industry.
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