A new biometric identification method is introduced in which a user “writes” his or her signature in the air. Accelerometers worn on a wrist device transmit acceleration data wirelessly to a host computer that processes the data and authenticates the user. This paper describes the use of curvature moments associated with 3D curves in both configuration space and velocity space as the features u...

The rival penalized competitive learning (RPCL) algorithm has been developed to make the clustering analysis on a set of sample data in which the number of clusters is unknown, and recent theoretical analysis shows that it can be constructed by minimizing a special kind of cost function on the sample data. In this paper, we use the Mahalanobis distance instead of the Euclidean distance in the c...

Supervised metric learning plays a substantial role in statistical classification. Conventional metric learning algorithms have limited utility when the training data and testing data are drawn from related but different domains (i.e., source domain and target domain). Although this issue has got some progress in feature-based transfer learning, most of the work in this area suffers from non-tr...

In speech processing, gender clustering and classification plays a major role. In both gender clustering and classification, selecting the feature is an important process and the often utilized feature for gender clustering and classification in speech processing is pitch. The pitch value of a male speech differs much from that of a female speech. Normally, there is a considerable frequency val...

The paper mainly studies static 2D face images through reconstructing 3D model by a specific algorithm. First, the paper need collect geometric features, and obtain the threedimensional space of false geodesic distance. Those are to emotional changes. Second, remove the relative feature extraction. Finally, compares the test sample and the training samples about the Mahalanobis distance. The ex...

Texture feature extraction operators, which comprise linear filtering, eventually followed by post-processing, are considered. The filters used are Laws’ masks, filters derived from well-known discrete transforms, and Gabor filters. The post-processing step comprises non-linear point operations and/or local statistics computation. The performance is measured by means of the Mahalanobis distance...

The classification of high dimensional data with kernel methods is considered in this article. Exploiting the emptiness property of high dimensional spaces, a kernel based on the Mahalanobis distance is proposed. The computation of the Mahalanobis distance requires the inversion of a covariance matrix. In high dimensional spaces, the estimated covariance matrix is ill-conditioned and its invers...