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Facial image analysis is an important computer vision topic as a first step for biometric applications like face recognition/verification. The ICAO specification defines criteria to assess suitability of facial images for later use in such tasks. This standard prohibits photographs showing occlusions, thus there is the need to detect occluded images automatically. In this work we present a novel algorithm...
In this paper, we combine two ideas: persistence-based clustering and the Heat Kernel Signature (HKS) function to obtain a multi-scale isometry invariant mesh segmentation algorithm. The key advantages of this approach is that it is tunable through a few intuitive parameters and is stable under near-isometric deformations. Indeed the method comes with feedback on the stability of the number of segments...
In this paper, we propose a novel face representation in which a face is represented in terms of dense Scale Invariant Feature Transform (d-SIFT) and shape contexts of the face image. The application of the representation in gender recognition has been investigated. There are four problems when applying the SIFT to facial gender recognition. (1) There may be only a few keypoints that can be found...
In this paper, we propose an efficient groupwise morphometric analysis to characterize morphological variations between healthy and pathological states. The proposed framework extends the work of Baloch in which a manifold for each anatomy was constructed by collecting lossless [transformation, residual] descriptors with various transformation parameters, and the optimal set of transformation parameters...
This paper reviews the concept of straight skeletons, which is well known in computational geometry, and applies it to binary shapes that are used in vision-based shape and object recognition. We devise a novel algorithm for computing discrete straight skeletons from binary input images, which is based on a polygonal approximation of the input shape and a hybrid method that combines continuous and...
Iannarelli's studies demonstrated that ear shape represents a biometric identifier able to authenticate people in the same way as more established biometrics, like face or voice for instance. However, not many researches can be found in literature about ear recognition. In most cases existing algorithms are borrowed from other biometric contexts. An example is PCA (Principal Component Analysis). Eigen-ears...
This article proposes a method for estimating the shape of masonry elements present in the facade of a Gothic building from a single image. Our approach takes as input a rectified image of a Gothic building facade and user-specified side information and provides a 3D model estimate of structural elements, e.g., doorways, windows, arches and cornices, within the facade as output. Facade estimation...
In this paper we address the problem of matching two 3D shapes by representing them using the eigenvalues and eigenvectors of the discrete diffusion operator. This provides representation framework useful for scale-space local shape descriptors and shape comparisons. We formally introduce diffusion embedding and we propose unit hypersphere normalizations of this embedding. We also propose a method...
This paper presents an automatic 3D head pose initialization scheme for a real-time face tracker with application to human-robot interaction. It has two main contributions. First, we propose an automatic 3D head pose and person specific face shape estimation, based on a 3D deformable model. The proposed approach serves to initialize our real-time 3D face tracker. What makes this contribution very...
Image encoding using interest points is a common technique in computer vision. In this paper we present a scale and rotation invariant shape centered interest point (SCIP) detector. By means of detecting singularities in Gradient Vector Flow (GVF) fields we find points of high symmetry in the image. Due to the nature of the underlying GVF field we can employ our features to group together edge-based...
In this paper we present several information-theoretic similiarity measures for shape retrieval in combination with non-rigid registration processes. The challenging property of these measures is that they are bypass divergences, that is, do not require the estimation of the probability density function for each shape. After presenting the dissimilarities and proposing some new ones, we analyze their...
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