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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Alexander M. Bronstein
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Article
Deep fused two-step cross-modal hashing with multiple semantic supervision
Existing cross-modal hashing methods ignore the informative multimodal joint information and cannot fully exploit the semantic labels. In this paper, we propose a deep fused two-step cross-modal hashing (DFTH)...
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Article
Intra-class low-rank regularization for supervised and semi-supervised cross-modal retrieval
Cross-modal retrieval aims to retrieve related items across different modalities, for example, using an image query to retrieve related text. The existing deep methods ignore both the intra-modal and inter-mod...
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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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Reference Work Entry In depth
Manifold Intrinsic Similarity
Nonrigid shapes are ubiquitous in nature and are encountered at all levels of life, from macro to nano. The need to model such shapes and understand their behavior arises in many applications in imaging scienc...
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Article
Equi-affine Invariant Geometry for Shape Analysis
Traditional models of bendable surfaces are based on the exact or approximate invariance to deformations that do not tear or stretch the shape, leaving intact an intrinsic geometry associated with it. These ge...
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Chapter
Group-Valued Regularization for Motion Segmentation of Articulated Shapes
Motion-based segmentation is an important tool for the analysis of articulated shapes. As such, it plays an important role in mechanical engineering, computer graphics, and computer vision. In this chapter, we...
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Chapter
Stable Semi-local Features for Non-rigid Shapes
Feature-based analysis is becoming a very popular approach for geometric shape analysis. Following the success of this approach in image analysis, there is a growing interest in finding analogous methods in th...
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Book and Conference Proceedings
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Chapter and Conference Paper
Equi-affine Invariant Geometries of Articulated Objects
We introduce an (equi-)affine invariant geometric structure by which surfaces that go through squeeze and shear transformations can still be properly analyzed. The definition of an affine invariant metric enab...
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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
Feature-Based Methods in 3D Shape Analysis
The computer vision and pattern recognition communities have recently witnessed a surge in feature-based methods for numerous applications including object recognition and image retrieval. Similar concepts and...
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Reference Work Entry In depth
Manifold Intrinsic Similarity
Non-rigid shapes are ubiquitous in Nature and are encountered at all levels of life, from macro to nano. The need to model such shapes and understand their behavior arises in many applications in imaging scien...
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Article
A Gromov-Hausdorff Framework with Diffusion Geometry for Topologically-Robust Non-rigid Shape Matching
In this paper, the problem of non-rigid shape recognition is studied from the perspective of metric geometry. In particular, we explore the applicability of diffusion distances within the Gromov-Hausdorff fram...
