Scale Space and Variational Methods in Computer Vision
Third International Conference, SSVM 2011, Ein-Gedi, Israel, May 29 – June 2, 2011, Revised Selected Papers
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20 Result(s)
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Chapter and Conference Paper
Sparse Models for Intrinsic Shape Correspondence
We present a novel sparse modeling approach to non-rigid shape matching using only the ability to detect repeatable regions. As the input to our algorithm, we are given only two sets of regions in two shapes; ...
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Book and Conference Proceedings
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Chapter and Conference Paper
Stable Spectral Mesh Filtering
The rapid development of 3D acquisition technology has brought with itself the need to perform standard signal processing operations such as filters on 3D data. It has been shown that the eigenfunctions of the...
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Chapter and Conference Paper
A Correspondence-Less Approach to Matching of Deformable Shapes
Finding a match between partially available deformable shapes is a challenging problem with numerous applications. The problem is usually approached by computing local descriptors on a pair of shapes and then ...
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Chapter and Conference Paper
Photometric Heat Kernel Signatures
In this paper, we explore the use of the diffusion geometry framework for the fusion of geometric and photometric information in local heat kernel signature shape descriptors. Our construction is based on the ...
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Chapter and Conference Paper
Deformable Shape Retrieval by Learning Diffusion Kernels
In classical signal processing, it is common to analyze and process signals in the frequency domain, by representing the signal in the Fourier basis, and filtering it by applying a transfer function on the Fou...
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Chapter and Conference Paper
Putting the Pieces Together: Regularized Multi-part Shape Matching
Multi-part shape matching is an important class of problems, arising in many fields such as computational archaeology, biology, geometry processing, computer graphics and vision. In this paper, we address the ...
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Chapter and Conference Paper
Shape Palindromes: Analysis of Intrinsic Symmetries in 2D Articulated Shapes
Analysis of intrinsic symmetries of non-rigid and articulated shapes is an important problem in pattern recognition with numerous applications ranging from medicine to computational aesthetics. Considering art...
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Chapter and Conference Paper
Discrete Minimum Distortion Correspondence Problems for Non-rigid Shape Matching
Similarity and correspondence are two fundamental archetype problems in shape analysis, encountered in numerous application in computer vision and pattern recognition. Many methods for shape similarity and cor...
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Chapter and Conference Paper
Group-Valued Regularization Framework for Motion Segmentation of Dynamic Non-rigid Shapes
Understanding of articulated shape motion plays an important role in many applications in the mechanical engineering, movie industry, graphics, and vision communities. In this paper, we study motion-based segm...
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Chapter and Conference Paper
Spatially-Sensitive Affine-Invariant Image Descriptors
Invariant image descriptors play an important role in many computer vision and pattern recognition problems such as image search and retrieval. A dominant paradigm today is that of “bags of features”, a repres...
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Chapter and Conference Paper
Regularized Partial Matching of Rigid Shapes
Matching of rigid shapes is an important problem in numerous applications across the boundary of computer vision, pattern recognition and computer graphics communities. A particularly challenging setting of th...
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Chapter
Story of Cinderella
In this chapter, we address the question of what are the facial measures one could use in order to distinguish between people. Our starting point is the fact that the expressions of our face can, in most cases...
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Chapter and Conference Paper
Paretian Similarity for Partial Comparison of Non-rigid Objects
In this paper, we address the problem of partial comparison of non-rigid objects. We introduce a new class of set-valued distances, related to the concept of Pareto optimality in economics. Such distances allo...
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Chapter and Conference Paper
Matching Two-Dimensional Articulated Shapes Using Generalized Multidimensional Scaling
We present a theoretical and computational framework for matching of two-dimensional articulated shapes. Assuming that articulations can be modeled as near-isometries, we show an axiomatic construction of an a...
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Chapter and Conference Paper
Robust Expression-Invariant Face Recognition from Partially Missing Data
Recent studies on three-dimensional face recognition proposed to model facial expressions as isometries of the facial surface. Based on this model, expression-invariant signatures of the face were constructed ...
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Chapter and Conference Paper
Facetoface: An Isometric Model for Facial Animation
A geometric framework for finding intrinsic correspondence between animated 3D faces is presented. We model facial expressions as isometries of the facial surface and find the correspondence between two faces ...
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Chapter and Conference Paper
Isometric Embedding of Facial Surfaces into \(\mathbb{S}^{\rm 3}\)
The problem of isometry-invariant representation and comparison of surfaces is of cardinal importance in pattern recognition applications dealing with deformable objects. Particularly, in three-dimensional fac...
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Chapter and Conference Paper
Face Recognition from Facial Surface Metric
Recently, a 3D face recognition approach based on geometric invariant signatures, has been proposed. The key idea is a representation of the facial surface, invariant to isometric deformations, such as those r...
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Chapter and Conference Paper
Expression-Invariant 3D Face Recognition
We present a novel 3D face recognition approach based on geometric invariants introduced by Elad and Kimmel. The key idea of the proposed algorithm is a representation of the facial surface, invariant to isome...
