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Facial appearance changes because uncontrolled variations of facial appearances due to illumination, pose, expression, occlusion of non-cooperative subjects and subject-to-camera distance need to be handled to allow for successful recognition. This paper presents a novel image quality assessment model. The model is designed to reduce the influence which is caused by the degradation of facial image...
Visual interpretation of natural pointing gestures is essential in a human robot interaction scenario. Both hands and head are involved in pointing behaviors. Given the color images acquired by a web camera and the depth data by a TOF range camera, we perform visual tracking of the head and hands in 3D space. We investigate both the Head-Finger Line (HFL) and the forearm orientation as the estimation...
Independent component analysis (ICA) is a basic method widely used in expression feature extraction and recognition. In this paper, combined with the characteristic of ICA, a novel method based on Scatter-Difference Matrix and Independent Component Analysis is presented. With the help of Scatter-Difference matrix, expression feature can be identified and classified effectively by ICA.Firstly, the...
Based on UDP and MFA, we propose a new unsupervised feature extraction algorithm, LMP (Local Marginal Projection), which is built on local quality. It measures the non-local quantities by the nearest sample between two locals. The goal of LMP is to find a projection that can maximize the distance of the sample in the same local and in different locals, in which case, the data can be projected into...
A new feature extraction method based on manifold learning is proposed for face recognition in the paper; its criterion function is characterized by maximizing the difference between the nonlocal scatter and the local scatter. The novel method is called two-directional two-dimensional marginal discriminant projection ((2D)2MDP), which simultaneously works image matrix in the row direction and in the...
Based on manifold learning, a new feature extraction method is proposed for face recognition in the paper. The new method is called two-directional two-dimensional unsupervised discriminant projection ((2D)2UDP), which simultaneously works image matrix in the row direction and in the column direction for feature extraction. The experimental results on ORL face databases and AR face databases indicate...
This paper proposes a two-phase algorithm of image projection discriminant analysis. The new discriminant method is composed of feature extraction by on maximum margin criterion (MMC) and Fisher discriminant analysis (FDA). The algorithm includes two stages: firstly, the feature extraction based on maximum margin criterion (MMC) is employed to condense the dimension of image matrix; Then Fisher discriminant...
Graphical password (i.e., image based authentication) is considered as a promising alternative to traditional textual password for mobile devices, to achieve better tradeoff between usability and security. However, previous proposals of graphical password have the limitation of limited entropy. In this paper, we propose a new scheme incorporating user face based authentication into the association-based...
A improved method of feature extraction based on kernel maximum margin criterion (KMMC) is presented for face recognition in this paper, i.e. a simple algorithm of uncorrected optimal discriminant vectors in kernel feature space is proposed for nonlinear feature extraction. The proposed method has more powerful capability to eliminate the statistical correlation between feature vectors and its mathematical...
In this paper, an image-based fast 3D facial modeling algorithm is presented. Different from traditional complex stereo vision procedure, our new method needs only one frontal image for fast 3D modeling without any camera calibration. To extract frontal feature points effectively, we propose an improved Active Shape Models (ASM) method. We can calculate the lateral parameters and estimate the depth...
For nonlinear feature extraction, a new feature extraction method based on kernel maximum margin criterion (KMMC) is presented in this paper, i.e., an algorithm of statistically uncorrelated optimal discriminant vectors in kernel feature space is proposed in the paper. The proposed method has more powerful capability to eliminate the statistical correlation between features and improve efficiency...
With the help of two-dimensional independent component analysis (2DICA) based on wavelet-transform (WT-2DICA), high-order statistical information can be extracted effectively, and experimental results on ORL (Olivetti Research Laboratory) and Yale face database show that correct recognition rate by WT-2DICA is good. However, this method is not valid to damaged images. Category information by improved...
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