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A search engine for 3d models
 ACM Transactions on Graphics
, 2003
"... As the number of 3D models available on the Web grows, there is an increasing need for a search engine to help people find them. Unfortunately, traditional textbased search techniques are not always effective for 3D data. In this paper, we investigate new shapebased search methods. The key challen ..."
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Cited by 237 (21 self)
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As the number of 3D models available on the Web grows, there is an increasing need for a search engine to help people find them. Unfortunately, traditional textbased search techniques are not always effective for 3D data. In this paper, we investigate new shapebased search methods. The key challenges are to develop query methods simple enough for novice users and matching algorithms robust enough to work for arbitrary polygonal models. We present a webbased search engine system that supports queries based on 3D sketches, 2D sketches, 3D
Shape Distributions
 ACM Transactions on Graphics
, 2002
"... this paper, we propose and analyze a method for computing shape signatures for arbitrary (possibly degenerate) 3D polygonal models. The key idea is to represent the signature of an object as a shape distribution sampled from a shape function measuring global geometric properties of an object. The pr ..."
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Cited by 195 (1 self)
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this paper, we propose and analyze a method for computing shape signatures for arbitrary (possibly degenerate) 3D polygonal models. The key idea is to represent the signature of an object as a shape distribution sampled from a shape function measuring global geometric properties of an object. The primary motivation for this approach is to reduce the shape matching problem to the comparison of probability distributions, which is simpler than traditional shape matching methods that require pose registration, feature correspondence, or model fitting
Matching 3D Models with Shape Distributions
"... Measuring the similarity between 3D shapes is a fundamental problem, with applications in computer vision, molecular biology, computer graphics, and a variety of other fields. A challenging aspect of this problem is to find a suitable shape signature that can be constructed and compared quickly, whi ..."
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Cited by 177 (7 self)
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Measuring the similarity between 3D shapes is a fundamental problem, with applications in computer vision, molecular biology, computer graphics, and a variety of other fields. A challenging aspect of this problem is to find a suitable shape signature that can be constructed and compared quickly, while still discriminating between similar and dissimilar shapes. In this paper, we propose and analyze a method for computing shape signatures for arbitrary (possibly degenerate) 3D polygonal models. The key idea is to represent the signature of an object as a shape distribution sampled from a shape function measuring global geometric properties of an object. The primary motivation for this approach is to reduce the shape matching problem to the comparison of probability distributions, which is a simpler problem than the comparison of 3D surfaces by traditional shape matching methods that require pose registration, feature correspondence, or model fitting. We find that the dissimilarities be...
A Reflective Symmetry Descriptor for 3D Models
 ALGORITHMICA
, 2004
"... Computing reflective symmetries of 2D and 3D shapes is a classical problem in computer vision and computational geometry. Most prior work has focused on finding the main axes of symmetry, or determining that none exists. In this paper we introduce a new reflective symmetry descriptor that represent ..."
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Cited by 60 (7 self)
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Computing reflective symmetries of 2D and 3D shapes is a classical problem in computer vision and computational geometry. Most prior work has focused on finding the main axes of symmetry, or determining that none exists. In this paper we introduce a new reflective symmetry descriptor that represents a measure of reflective symmetry for an arbitrary 3D model for all planes through the model’s center of mass (even if they are not planes of symmetry). The main benefits of this new shape descriptor are that it is defined over a canonical parameterization (the sphere) and describes global properties of a 3D shape. We show how to obtain a voxel grid from arbitrary 3D shapes and, using Fourier methods, we present an algorithm that computes the symmetry descriptor in O(N 4 log N) time for an N × N × N voxel grid and computes a multiresolution approximation in O(N 3 log N) time. In our initial experiments, we have found that the symmetry descriptor is insensitive to noise and stable under point sampling. We have also found that it performs well in shape matching tasks, providing a measure of shape similarity that is orthogonal to existing methods.
A Comparison of Text and Shape Matching for Retrieval of Online 3D Models
 In Proc. European Conference on Digital Libraries
, 2004
"... Because of recent advances in graphics hard and software, both the production and use of 3D models are increasing at a rapid pace. As a result, a large number of 3D models have become available on the web, and new research is being done on 3D model retrieval methods. Query and retrieval can be d ..."
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Cited by 13 (1 self)
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Because of recent advances in graphics hard and software, both the production and use of 3D models are increasing at a rapid pace. As a result, a large number of 3D models have become available on the web, and new research is being done on 3D model retrieval methods. Query and retrieval can be done solely based on associated text, as in image retrieval, for example (e.g. Google Image Search [1] and [2, 3]). Other research focuses on shapebased retrieval, based on methods that measure shape similarity between 3D models (e.g., [4]).
N.A.Thacker, P.Courtney and A.Clark. Last updated
"... Many of the vision algorithms described in the literature are tested on a very small number of images. It is generally agreed that algorithms need to be tested on much larger numbers if any statistically meaningful measure of performance is to be obtained. However, these tests are rarely performed; ..."
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Many of the vision algorithms described in the literature are tested on a very small number of images. It is generally agreed that algorithms need to be tested on much larger numbers if any statistically meaningful measure of performance is to be obtained. However, these tests are rarely performed; in our opinion this is normally due to two reasons. Firstly, the scale of the testing problem when high levels of reliability are sought, since it is the
Matching 3D Models with Shape Distributions
"... Measuring the similarity between 3D shapes is a fundamental problem, with applications in computer vision, molecular biology, computer graphics, and a variety of other fields. A challenging aspect of this problem is to find a suitable shape signature that can be constructed and compared quickly, whi ..."
Abstract
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Measuring the similarity between 3D shapes is a fundamental problem, with applications in computer vision, molecular biology, computer graphics, and a variety of other fields. A challenging aspect of this problem is to find a suitable shape signature that can be constructed and compared quickly, while still discriminating between similar and dissimilar shapes. In this paper, we propose and analyze a method for computing shape signatures for arbitrary (possibly degenerate) 3D polygonal models. The key idea is to represent the signature of an object as a shape distribution sampled from a shape function measuring global geometric properties of an object. The primary motivation for this approach is to reduce the shape matching problem to the comparison of probability distributions, which is simpler than traditional shape matching methods that require pose registration, feature correspondence, or model fitting. We find that the dissimilarities between sampled distributions of simple shape functions (e.g., the distance between two random points on a surface) provide a robust method for discriminating between classes of objects (e.g., cars versus airplanes) in a moderately sized database, despite the presence of arbitrary translations, rotations, scales, mirrors, tessellations, simplifications, and model degeneracies. They can be evaluated quickly, and thus the proposed method could be applied as a preclassifier in an object recognition system or in an interactive contentbased retrieval application. 1
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"... Clinically, the assessment of human cerebral cortical thickness (the thickness of the cortical grey matter ribbon) has massive importance in the determination of pathology and in assessing the processes of “normal ” brain maturation and ageing. ..."
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Clinically, the assessment of human cerebral cortical thickness (the thickness of the cortical grey matter ribbon) has massive importance in the determination of pathology and in assessing the processes of “normal ” brain maturation and ageing.
Retinal Sampling, Feature Detection and Saccades;
"... This paper applies statistical design principles to a simple biological model of human vision so that we can more clearly interpret the apparent role of eye saccades. In doing so we show that many structural features of the biological system (such as the optical geometry of the retina) are not compl ..."
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This paper applies statistical design principles to a simple biological model of human vision so that we can more clearly interpret the apparent role of eye saccades. In doing so we show that many structural features of the biological system (such as the optical geometry of the retina) are not complications which need to be surmounted or accomodated by later processing, but very good strategies for minimising the resources required to construct a working image recognition system. Therefore, (and as expected) the structure we see can very easily be explained by evolutionary pressures. The work also suggests specific forms for intermediate computed quantities, chosen to match the representation of signals as pulse sequences in neuronal systems. The ideas presented have implications for the construction of artificial (computer) vision systems. The computational model is very closely related to (but not based upon) SIFT, but more strongly based on a consideration of vision as a process of measurment while also linking the idea of multiscale analysis with biological structure.
A Statistical Perspective.
"... This paper applies statistical design principles to a simple biological model of human vision so that we can more clearly interpret the apparent role of eye saccades. In doing so we show that many structural features of the biological system (such as the optical geometry of the retina) are not compl ..."
Abstract
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This paper applies statistical design principles to a simple biological model of human vision so that we can more clearly interpret the apparent role of eye saccades. In doing so we show that many structural features of the biological system (such as the optical geometry of the retina) are not complications which need to be surmounted or accomodated by later processing, but very good strategies for minimising the resources required to construct a working image recognition system. Therefore, (and as expected) the structure we see can very easily be explained by evolutionary pressures. The work also suggests specific forms for intermediate computed quantities, chosen to match the representation of signals as pulse sequences in neuronal systems. The ideas presented have implications for the construction of artificial (computer) vision systems. The computational model is very closely related to (but not based upon) SIFT, but more strongly based on a consideration of vision as a process of measurment while also linking the idea of multiscale analysis with biological structure.