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This paper presents a view independent video-based face recognition method using posterior probability in Kernel Fisher Discriminant (KFD) space. In practical environment, the view of faces changes dynamically. The robustness to view changes is required for video-based face recognition in practical environment. Since the view changes induces large non-linear variation, kernel-based methods are appropriate...
Symmetry is a fundamental structure that is found to some extent in all images. It is thought to be an important factor in the human visual system for obtaining understanding and extracting semantics from visual material. This paper describes a method of detecting axes of reflective symmetry in faces that does not require prior assumptions about the image being analysed. The approach is derived from...
In this paper, an efficient iris segmentation method for recognition is described. The method is based on crossed chord theorem and zigzag collarette area. We select the zigzag collarette region as personal identification pattern, which can remove unnecessary areas and get good recognition rate. Zigzag collarette area is one of the most important parts of iris complex pattern. It is insensitive to...
This paper describes a novel method for palmprint recognition based on registration information and 2D Gabor features. After preprocessing, a unified coordinate system is constructed for each palmprint image and used to guide ROI extraction. A multi-scale matching strategy is employed to match registration information and 2D Gabor features. In the first two levels, registration information is extracted...
In this paper we analyse the effects that JPEG and JPEG2000 compression have on subspace appearance-based face recognition algorithms. This is the first comprehensive study of standard JPEG2000 compression effects on face recognition, as well as an extension of existing experiments for JPEG compression. A wide range of bitrates (compression ratios) was used on probe images and results are reported...
In this paper we present a technique for predicting the 2D human body joints and limbs position in monocular image sequences, and reconstructing its corresponding 3D postures using information provided by a 3D action model. This method is used in a framework based on particle filtering, for the automatic tracking and reconstruction of the 3D human body postures. A set of the reconstructed postures...
We present a technique for dimension reduction. The technique uses a gradient descent approach to attempt to sequentially find orthogonal vectors such that when the data is projected onto each vector the classification error is minimised. We make no assumptions about the structure of the data and the technique is independent of the classifier model used. Our approach has advantages over other dimensionality...
Retinal vessel extraction has become an important task of medical image processing applications in order to diagnose ocular diseases. In this paper, a novel methodology is proposed to extract vessels automatically from retinal angiographies. The proposed methodology has been implemented by means of Cellular Neural Networks techniques to take advantage of their capabilities of massively parallel processing...
It has been established that information distinguishing one human face from another is contained to a large extent in the Fourier domain phase component of the facial image. However, to date, formal statistical models for this component have not been deployed in face recognition tasks. In this paper we introduce a model-based approach using Gaussian mixture models (GMM) for the phase component for...
A novel and efficient approach to facial expression classification based on the belief theory and data fusion is presented and discussed. The considered expressions correspond to three (joy, surprise, disgust) of the six universal emotions as well as the neutral expression. A robust contour segmentation technique is used to generate an expression skeleton with facial permanent features (mouth, eyes...
In this paper, we propose an uncorrelated, weighted LDA (UWLDA) technique for face recognition. The UWLDA extends the uncorrelated LDA (ULDA) technique by integrating the weighted pairwise Fisher criterion and nullspace LDA (NLDA), while retaining all merits of ULDA. Experiments compare the proposed algorithm to other face recognition methods that employ linear dimensionality reduction such as Eigenfaces,...
In this paper, we propose a novel heteroscedastic weighted kernel discriminant analysis (HW-KDA) method that extends the linear discriminant analysis (LDA) to deal explicitly with heteroscedasticity and nonlinearity of the face pattern’s distribution by integrating the weighted pairwise Chernoff criterion and Kernel trick. The proposed algorithm has been tested, in terms of classification rate performance,...
In this paper, a supervised feature extraction method having both non-negative bases and weights is proposed. The idea is to extend the Non-negative Matrix Factorization (NMF) algorithm in order to extract features that enforce not only the spatial locality, but also the separability between classes in a discriminant manner. The proposed method incorporates discriminant constraints inside the NMF...
For databases of facial images, where each subject has only a few images, the query precision of interactive retrieval suffers from the problem of extremely small class sizes. A novel method is proposed to relieve this problem by applying partial relevance to the interactive retrieval. This work extends an existing content-based image retrieval system, PicSOM, by relaxing the relevance criterion in...
This paper presents a new approach to efficient and effective personal identification for the security of network access by combining techniques in biometrics and mobile computing. To overcome the limitations of the existing password-based authentication services on the Internet, we propose a dynamic feature selection scheme to extract multiple personal features and integrate them in a hierarchical...
An efficient algorithm to iris segmentation and its application to automatic and non-intrusive gaze tracking and vigilance estimation is presented and discussed. A luminance gradient technique is used to fit the irises from face images. A robust preprocessing which mimics the human retina is used in such a way that a robust system to luminance variations is obtained and contrast enhancement is achieved...
In this paper, we present a new statistical projection-based face recognition method, called Bilinear Discriminant Analysis (BDA). The proposed technique effectively combines two complementary versions of Two-Dimensional-Oriented Linear Discriminant Analysis (2DoLDA), namely Column-Oriented Linear Discriminant Analysis (CoLDA) and Row-Oriented Linear Discriminant Analysis (RoLDA). BDA relies on the...
Adaptation to dynamically changing environment is very important since advanced applications become pervasive and ubiquitous. This paper addresses a novel method of adaptive object recognition using environmental context-awareness and genetic algorithm and t-test. The proposed method tries to distinguish the category of input environment and decides an optimal classifier combination structure accordingly...
In this paper, the framework and implementation of a real time multi-scale face detection system using appearance-based learning method and multi-pose hybrid learning approach. Multiple scale and pose based object detection is attractive since it could accumulate the face models by autonomous learning process. Face image, however, can be approximated even though it is represented with many scales...
Statistical dependence of classifiers has recently been shown to improve accuracy over statistically independent classifiers. In this paper, we focus on the verification application and theoretically analyze the AND fusion rule to find the favorable conditional dependence that improves the fusion accuracy over conditionally independent classifiers. Based on this analysis, we come with a method to...
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