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This paper proposes, an efficient method for text independent writer identification using a codebook. The occurrence histogram of the shapes in the codebook is used to create a feature vector for the handwriting. There is a wide variety of different shapes in the connected components obtained from handwriting. Small fragments of connected components should be used to avoid complex patterns. A new...
We have at our disposal a large database containing images of various configurations of coplanar circles, randomly laid-out, called “Bubble Tags”. The images are taken from different viewpoints. Given a new image (query image), the goal is to find in the database the image containing the same bubble tag as the query image. We propose representing the images through projective invariant signatures...
We present a 3D face reconstruction system that takes as input either one single view or several different views. Given a facial image, we first classify the facial pose into one of five predefined poses, then detect two anchor points that are then used to detect a set of predefined facial landmarks. Based on these initial steps, for a single view we apply a warping process using a generic 3D face...
A novel block-based bag of words (BBoW) method is proposed for robust face recognition. In our approach, a face image is partitioned into multiple blocks, dense SIFT features are then calculated and vector quantized into different codewords on each block respectively. Finally, histograms of codeword distribution on each local block are concatenated to represent the face image. Experimental results...
Automatic recognition of printed mathematical symbols is a fundamental problem for recognition of mathematical expressions. Several classification techniques has been previously used, but there are very few works that compare different classification techniques on the same database and with the same experimental conditions. In this work we have tested classical and novelty classification techniques...
We propose a novel exemplar based method to estimate 3D human poses from single images by using only the joint correspondences. Due to the inherent depth ambiguity, estimating 3D poses from a monocular view is a challenging problem. We solve the problem by searching through millions of exemplars for optimal poses. Compared with traditional parametric schemes, our method is able to handle very large...
The aim of this paper is to propose tools for statistical analysis of shape families using morphological operators. Given a series of shape families (or shape categories), the approach consists in empirically computing shape statistics (i.e., mean shape and variance of shape) and then to use simple algorithms for random shape generation, for empirical shape confidence boundaries computation and for...
In this paper, we address the problem of gait based gender classification. The Gabor feature which is a new attempt for gait analysis, not only improves the robustness to the segmental noise, but also provides a feasible way to purge the additional influence factors like clothing and carrying condition changes before supervised learning. Furthermore, through the agency of Maximization of Mutual Information...
In this paper we present a fully automatic system for face recognition across pose where no frontal view is needed in enrollment or test. The system uses three Active Appearance Models(AAMs): the first one is a generic multi resolution AAM, while the remaining ones are trained to cope with left/right variations (i.e. pose-dependent AAMs). During the fitting stage, pose is automatically estimated using...
Personal identification based on finger vein patterns is a newly developed biometrics technique and several practical systems have been deployed recent years. We developed a finger vein verification system for checking attendance and have collected a database of 0.8 million finger vein samples. Based on the database, we proposed a person retrieval solution for searching an image in the database and...
Patch-based face recognition is a recent method which uses the idea of analyzing face images locally, in order to reduce the effects of illumination changes and partial occlusions. Feature fusion and decision fusion are two distinct ways to make use of the extracted local features. Apart from the well-known decision fusion methods, a novel approach for calculating weights for the weighted sum rule...
Existing face recognition approaches are mostly developed based on adult faces which may not work well in distinguishing faces of kids. Especially, baby faces tend to have common features such as round cheeks and chins, so that current face recognition engines often fail to differentiate them. In this paper, we present methods for discriminating baby faces from adult faces, and for training a special...
In this paper, a kernel uncorrelated adjacent-class discriminant analysis (KUADA) approach is proposed for image recognition. The optimal nonlinear discriminant vector obtained by this approach can differentiate one class and its adjacent classes, i.e., its nearest neighbor classes, by constructing the specific between-class and within-class scatter matrices in kernel space using the Fisher criterion...
With growing attention to ensemble learning, in recent years various ensemble methods for face recognition have been proposed that show promising results. Among diverse ensemble construction approaches, random subspace method has received considerable attention in face recognition. Although random feature selection in random subspace method improves accuracy in general, it is not free of serious difficulties...
The sparse representation-based classifier (SRC) has been developed and shows great potential for pattern classification. This paper aims to gain a discriminative projection such that SRC achieves the optimum performance in the projected pattern space. We use the decision rule of SRC to steer the design of a dimensionality reduction method, which is coined the sparse representation classifier steered...
Spatial database contains a great deal of topological and directional semantics. But traditional spatial data query methods didn't make good use of these high level semantics. To overcome this conceptual gap, this paper proposes a spatial data query method based on sketch using 9-intersection model and Deep-Direction-Relation Matrix. This method integrates direction relations and topological relations...
In this paper, we develop a novel 3D face recognition algorithm based on Local Binary Pattern (LBP) representation under expression varieties. First, to enable the application of LBP representation framework, a special feature-based 3D face division scheme is proposed. Then, the LBP framework for 3D face representation is described, and the facial depth and normal information are extracted and encoded...
This paper presents an approach to the task of locating a group of buildings based solely on their relative spatial relationships. This situation can occur in the problem of conflation of a hand or machine drafted map to a satellite image or in matching of two images taken under different viewing conditions (the correspondence problem). Of importance to us is the general text-to-sketch problem where...
In this paper, we introduce a fingerprint authentication system for protecting the privacy of the fingerprint template stored in a database. The template, which is a binary fingerprint image after thinning, will be embedded with private personal data in the user enrollment phase. In the user authentication phase, these hidden personal data can be extracted from the stored template for verifying the...
In this paper, we introduce a new image database, consisting of examples of artists' work. Successful classification of this database suggests the capacity to automatically recognize an artist's aesthetic style. We utilize the notion of Transform-based Evolvable Features as a means of evolving features on the space, these features are then evaluated through a standard classifier. We obtain recognition...
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