Kernel Grassmannian distances and discriminant analysis for face recognition from image sets
We address the problem of face recognition from image sets, where subject-specific subspaces instead of image vectors are compared. Previous methods based on Grassmannian subspace distances mainly take linear subspaces as input. The non-linearity exists ...
A decision-boundary-oriented feature selection method and its application to face recognition
A novel feature selection scheme is proposed. We construct a piecewise linear decision boundary, and find a feature sub-space suitable to the constructed boundary. Experimental results show that the proposed scheme outperforms conventional algorithms ...
A new lower bound for evaluating the performances of sensor location algorithms
Locating sensors in 2D can be modelled as an Art Gallery problem. Tasks such as surveillance require observing or ''covering'' the interior of a polygon with a minimum number of sensors (IC, Interior Covering). Edge Covering (EC) is sufficient for tasks ...
Fast gesture recognition based on a two-level representation
Towards developing an interface for human-robot interaction, this paper proposes a two-level approach to recognise gestures which are composed of trajectories followed by different body parts. In a first level, individual trajectories are described by a ...
Cluster-based genetic segmentation of time series with DWT
A time series is composed of lots of data points, each of which represents a value at a certain time. Many phenomena can be represented by time series, such as electrocardiograms in medical science, gene expressions in biology and video data in ...
Shape from silhouette using topology-adaptive mesh deformation
We present a computationally efficient and robust shape from silhouette method based on topology-adaptive mesh deformation, which can produce accurate, smooth, and topologically consistent 3D mesh models of complex real objects. The deformation scheme ...
Enhanced supervised locally linear embedding
In this paper, a new nonlinear dimensionality reduction algorithm, called enhanced supervised locally linear embedding (ESLLE), is proposed. The ESLLE method attempts to make the interclass dissimilarity definitely larger than the intraclass ...
Palmprint verification using binary orientation co-occurrence vector
The development of accurate and robust palmprint verification algorithms is a critical issue in automatic palmprint authentication systems. Among various palmprint verification approaches, the orientation based coding methods, such as competitive code (...
Training data selection for improving discriminative training of acoustic models
This paper considers training data selection for discriminative training of acoustic models for large vocabulary continuous speech recognition (LVCSR). Three novel data selection approaches are proposed. First, the average phone accuracy over all ...
Least squares one-class support vector machine
In this paper, we reformulate a standard one-class SVM (support vector machine) and derive a least squares version of the method, which we call LS (least squares) one-class SVM. The LS one-class SVM extracts a hyperplane as an optimal description of ...
An improved Hough transform voting scheme utilizing surround suppression
The Hough transform has been a frequently used method for detecting lines in images. However, when applying Hough transform and derived algorithms using the standard Hough voting scheme on real-world images, the methods often suffer considerable ...
