Limits...
A Multimodal User Authentication System Using Faces and Gestures.

Choi H, Park H - Biomed Res Int (2015)

Bottom Line: Therefore, it can be a countermeasure when the physical information is exposed.We aim to investigate the potential possibility of using gestures as a signal for biometric system and the robustness of the proposed multimodal user authentication system.Through computational experiments on a public database, we confirm that gesture information can help to improve the authentication performance.

View Article: PubMed Central - PubMed

Affiliation: School of Electrical Engineering and Computer Science, Kyungpook National University, Deagu 702-701, Republic of Korea.

ABSTRACT
As a novel approach to perform user authentication, we propose a multimodal biometric system that uses faces and gestures obtained from a single vision sensor. Unlike typical multimodal biometric systems using physical information, the proposed system utilizes gesture video signals combined with facial images. Whereas physical information such as face, fingerprints, and iris is fixed and not changeable, behavioral information such as gestures and signatures can be freely changed by the user, similar to a password. Therefore, it can be a countermeasure when the physical information is exposed. We aim to investigate the potential possibility of using gestures as a signal for biometric system and the robustness of the proposed multimodal user authentication system. Through computational experiments on a public database, we confirm that gesture information can help to improve the authentication performance.

No MeSH data available.


Sample images from ChaLearn database: (a) first frames of 20 selected users, (b) image frames in a gesture video.
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC4515489&req=5

fig4: Sample images from ChaLearn database: (a) first frames of 20 selected users, (b) image frames in a gesture video.

Mentions: In order to confirm the performance of proposed system, we conducted experiments on the ChaLearn database [22], which was built for a gesture recognition competition. Although the data includes depth signals obtained from Kinect, we use only RGB signals because the proposed method is developed for a general vision sensor. Figure 4 shows some examples of the data. From the whole data set, we prepared three sets—A, B, and C—for experiments. Each set is composed of 80 video samples from 20 subjects; each subject makes his/her own unique gesture four times. Experiments are carried out for each set separately using 4-fold cross-validation. Three samples from each subject are used for gallery data and one sample is used for probe data. Therefore, total 12 experiments were carried out.


A Multimodal User Authentication System Using Faces and Gestures.

Choi H, Park H - Biomed Res Int (2015)

Sample images from ChaLearn database: (a) first frames of 20 selected users, (b) image frames in a gesture video.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4515489&req=5

fig4: Sample images from ChaLearn database: (a) first frames of 20 selected users, (b) image frames in a gesture video.
Mentions: In order to confirm the performance of proposed system, we conducted experiments on the ChaLearn database [22], which was built for a gesture recognition competition. Although the data includes depth signals obtained from Kinect, we use only RGB signals because the proposed method is developed for a general vision sensor. Figure 4 shows some examples of the data. From the whole data set, we prepared three sets—A, B, and C—for experiments. Each set is composed of 80 video samples from 20 subjects; each subject makes his/her own unique gesture four times. Experiments are carried out for each set separately using 4-fold cross-validation. Three samples from each subject are used for gallery data and one sample is used for probe data. Therefore, total 12 experiments were carried out.

Bottom Line: Therefore, it can be a countermeasure when the physical information is exposed.We aim to investigate the potential possibility of using gestures as a signal for biometric system and the robustness of the proposed multimodal user authentication system.Through computational experiments on a public database, we confirm that gesture information can help to improve the authentication performance.

View Article: PubMed Central - PubMed

Affiliation: School of Electrical Engineering and Computer Science, Kyungpook National University, Deagu 702-701, Republic of Korea.

ABSTRACT
As a novel approach to perform user authentication, we propose a multimodal biometric system that uses faces and gestures obtained from a single vision sensor. Unlike typical multimodal biometric systems using physical information, the proposed system utilizes gesture video signals combined with facial images. Whereas physical information such as face, fingerprints, and iris is fixed and not changeable, behavioral information such as gestures and signatures can be freely changed by the user, similar to a password. Therefore, it can be a countermeasure when the physical information is exposed. We aim to investigate the potential possibility of using gestures as a signal for biometric system and the robustness of the proposed multimodal user authentication system. Through computational experiments on a public database, we confirm that gesture information can help to improve the authentication performance.

No MeSH data available.