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Communicate with murphy iguard
Communicate with murphy iguard












communicate with murphy iguard

Park U., Jain A.K., Face matching and retrieval using soft biometrics, IEEE Trans.Jain A.K., Nandakumar K., Lu X., Park U., Integrating faces, fingerprints, and soft biometric traits for user recognition, Biometric Authentication Lecture Notes in Computer Science 3087 ( 2004) 259– 269.Our study demonstrates that holistic image features considered in this work provide reliable information for smartphone-based gender classification. In addition, the performance of our approach is consistent as it provides classification accuracy of 93.65% and 92.96% on the first and second datasets, respectively when multiple gestures are combined for gender recognition. Our experiments show that the approach achieves higher gender classification accuracy compared to the existing method.

communicate with murphy iguard

We have evaluated the performance of the proposed approach on two datasets, which consist of 2268 touch gestures from 126 subjects, collected using two different touchscreen devices. Finally, a k-nearest neighbor (k-NN) classifier recognizes the user's gender based on a subset of features identified through feature selection. The GIST descriptor-based features are then extracted from two-dimensional maps of the gesture attributes. These measurements are further enriched by deriving a secondary set of gesture attributes such as swipe length and point curvature. The primary behavioral data comprising readings from the accelerometer, gyroscope, and orientation sensors are acquired while the user interacts with the touchscreen device.

communicate with murphy iguard

This paper presents an approach for gender recognition in smartphones using touchscreen gestures performed by the user.














Communicate with murphy iguard