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91
Fitting Parameterized ThreeDimensional Models to Images
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1991
"... Modelbased recognition and motion tracking depends upon the ability to solve for projection and model parameters that will best fit a 3D model to matching 2D image features. This paper extends current methods of parameter solving to handle objects with arbitrary curved surfaces and with any nu ..."
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Cited by 289 (8 self)
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Modelbased recognition and motion tracking depends upon the ability to solve for projection and model parameters that will best fit a 3D model to matching 2D image features. This paper extends current methods of parameter solving to handle objects with arbitrary curved surfaces and with any number of internal parameters representing articulations, variable dimensions, or surface deformations. Numerical
Shock Graphs and Shape Matching
, 1998
"... We have been developing a theory for the generic representation of 2D shape, where structural descriptions are derived from the shocks (singularities) of a curve evolution process, acting on bounding contours. We now apply the theory to the problem of shape matching. The shocks are organized into a ..."
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Cited by 207 (34 self)
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We have been developing a theory for the generic representation of 2D shape, where structural descriptions are derived from the shocks (singularities) of a curve evolution process, acting on bounding contours. We now apply the theory to the problem of shape matching. The shocks are organized into a directed, acyclic shock graph, and complexity is managed by attending to the most significant (central) shape components first. The space of all such graphs is highly structured and can be characterized by the rules of a shock graph grammar. The grammar permits a reduction of a shock graph to a unique rooted shock tree. We introduce a novel tree matching algorithm which finds the best set of corresponding nodes between two shock trees in polynomial time. Using a diverse database of shapes, we demonstrate our system's performance under articulation, occlusion, and changes in viewpoint. Keywords: shape representation; shape matching; shock graph; shock graph grammar; subgraph isomorphism. 1 I...
A survey of freeform object representation and recognition techniques
 Computer Vision and Image Understanding
, 2001
"... Advances in computer speed, memory capacity, and hardware graphics acceleration have made the interactive manipulation and visualization of complex, detailed (and therefore large) threedimensional models feasible. These models are either painstakingly designed through an elaborate CAD process or re ..."
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Cited by 151 (1 self)
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Advances in computer speed, memory capacity, and hardware graphics acceleration have made the interactive manipulation and visualization of complex, detailed (and therefore large) threedimensional models feasible. These models are either painstakingly designed through an elaborate CAD process or reverse engineered from sculpted prototypes using modern scanning technologies and integration methods. The availability of detailed data describing the shape of an object offers the computer vision practitioner new ways to recognize and localize freeform objects. This survey reviews recent literature on both the 3D model building process and techniques used to match and identify freeform objects from imagery. c ○ 2001 Academic Press 1.
Computing Exact Aspect Graphs of Curved Objects: Algebraic Surfaces
"... This paper presents an algorithm for computing the exact aspect graph of an opaque solid bounded by a smooth algebraic surface and observed under orthographic projection. The algorithm uses curve tracing, cell decomposition, and ray tracing to construct the regions of the view sphere delineated by ..."
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Cited by 81 (10 self)
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This paper presents an algorithm for computing the exact aspect graph of an opaque solid bounded by a smooth algebraic surface and observed under orthographic projection. The algorithm uses curve tracing, cell decomposition, and ray tracing to construct the regions of the view sphere delineated by visual events. It has been fully implemented, and examples are presented.
Superquadrics for Segmenting and Modeling Range Data
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1997
"... We present a novel approach to reliable and efficient recovery of partdescriptions in terms of superquadric models from range data. We show that superquadrics can directly be recovered from unsegmented data, thus avoiding any presegmentation steps (e.g., in terms of surfaces). The approach is b ..."
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Cited by 57 (4 self)
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We present a novel approach to reliable and efficient recovery of partdescriptions in terms of superquadric models from range data. We show that superquadrics can directly be recovered from unsegmented data, thus avoiding any presegmentation steps (e.g., in terms of surfaces). The approach is based on the recoverandselect paradigm [10]. We present several experiments on real and synthetic range images, where we demonstrate the stability of the results with respect to viewpoint and noise.
Hierarchical Discriminant Analysis for Image Retrieval
 IEEE Trans. PAMI
, 1999
"... Abstract—A selforganizing framework for object recognition is described. We describe a hierarchical database structure for image retrieval. The SelfOrganizing Hierarchical Optimal Subspace Learning and Inference Framework (SHOSLIF) system uses the theories of optimal linear projection for automati ..."
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Cited by 47 (3 self)
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Abstract—A selforganizing framework for object recognition is described. We describe a hierarchical database structure for image retrieval. The SelfOrganizing Hierarchical Optimal Subspace Learning and Inference Framework (SHOSLIF) system uses the theories of optimal linear projection for automatic optimal feature derivation and a hierarchical structure to achieve a logarithmic retrieval complexity. A SpaceTessellation Tree is automatically generated using the Most Expressive Features (MEFs) and the Most Discriminating Features (MDFs) at each level of the tree. The major characteristics of the proposed hierarchical discriminant analysis include: 1) avoiding the limitation of global linear features (hyperplanes as separators) by deriving a recursively betterfitted set of features for each of the recursively subdivided sets of training samples; 2) generating a smaller tree whose cell boundaries separate the samples along the class boundaries better than the principal component analysis, thereby giving a better generalization capability (i.e., better recognition rate in a disjoint test); 3) accelerating the retrieval using a tree structure for data pruning, utilizing a different set of discriminant features at each level of the tree. We allow for perturbations in the size and position of objects in the images through learning. We demonstrate the technique on a large image database of widely varying realworld objects taken in natural settings, and show the applicability of the approach for variability in position, size, and 3D orientation. This paper concentrates on the hierarchical partitioning of the feature spaces. Index Terms—Principal component analysis, discriminant analysis, hierarchical image database, image retrieval, tessellation, partitioning, object recognition, face recognition, complexity with large image databases.
Hierarchical discriminant regression
 IEEE Trans. Pattern Anal. Mach. Intell
, 2000
"... AbstractÐThe main motivation of this paper is to propose a new classification and regression method for challenging highdimensional data. The proposed new technique casts classification problems (class labels as output) and regression problems (numeric values as output) into a unified regression pro ..."
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Cited by 46 (24 self)
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AbstractÐThe main motivation of this paper is to propose a new classification and regression method for challenging highdimensional data. The proposed new technique casts classification problems (class labels as output) and regression problems (numeric values as output) into a unified regression problem. This unified view enables classification problems to use numeric information in the output space that is available for regression problems but are traditionally not readily available for classification problemsÐdistance metric among clustered class labels for coarse and fine classifications. A doubly clustered subspacebased hierarchical discriminating regression (HDR) method is proposed in this work. The major characteristics include: 1) Clustering is performed in both output space and input space at each internal node, termed ªdoubly clustered.º Clustering in the output space provides virtual labels for computing clusters in the input space. 2) Discriminants in the input space are automatically derived from the clusters in the input space. These discriminants span the discriminating subspace at each internal node of the tree. 3) A hierarchical probability distribution model is applied to the resulting discriminating subspace at each internal node. This realizes a coarsetofine approximation of probability distribution of the input samples, in the hierarchical discriminating subspaces. No global distribution models are assumed. 4) To relax the per class sample requirement of traditional discriminant analysis techniques, a samplesize dependent negativeloglikelihood (NLL) is introduced. This new technique is designed for automatically dealing with smallsample applications, largesample applications, and unbalancedsample applications. 5) The execution of HDR method is fast, due to the empirical logarithmic time complexity of the HDR algorithm. Although the method is applicable to any data, we report the experimental results for three types of data: synthetic data for examining the nearoptimal performance, large raw faceimage data bases, and traditional databases with manually selected features along with a comparison with some major existing methods, such as CART,
Automatic detection of human nudes
 International Journal of Computer Vision
, 1999
"... This paper demonstrates an automatic system for telling whether there are human nudes present in an image. The system marks skinlike pixels using combined color and texture properties. These skin regions are then fed to a specialized grouper, which attempts to group a human figure using geometric c ..."
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Cited by 38 (3 self)
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This paper demonstrates an automatic system for telling whether there are human nudes present in an image. The system marks skinlike pixels using combined color and texture properties. These skin regions are then fed to a specialized grouper, which attempts to group a human figure using geometric constraints on human structure. If the grouper finds a sufficiently complex structure, the system decides a human is present. The approach is shown to be effective for a wide range of shades and colors of skin and human configurations. This approach offers an alternate view of object recognition, where an object model is an organized collection of grouping hints obtained from a combination of constraints on color and texture and constraints on geometric properties such as the structure of individual parts and the relationships between parts. The system demonstrates excellent performance on a test set of 565 uncontrolled images of human nudes, mostly obtained from the internet, and 4289 assorted control images, drawn from a wide variety of sources.
Recognition Using Region Correspondences
 International Journal of Computer Vision
, 1995
"... A central problem in object recognition is to determine the transformation that relates the model to the image, given some partial correspondence between the two. This is useful in determining whether an object is present in an image, and if so, determining where the object is. We present a novel me ..."
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Cited by 34 (7 self)
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A central problem in object recognition is to determine the transformation that relates the model to the image, given some partial correspondence between the two. This is useful in determining whether an object is present in an image, and if so, determining where the object is. We present a novel method of solving this problem that uses region information. In our approach the model is divided into volumes, and the image is divided into regions. Given a match between subsets of volumes and regions (without any explicit correspondence between different pieces of the regions) the alignment transformation is computed. The method applies to planar objects under similarity, affine, and projective transformations and to projections of 3D objects undergoing affine and projective transformations. 1 Introduction A fundamental problem in recognition is pose estimation. Given a correspondence between some portions of an object model and some portions of an image, determine the transformation th...
The 3L Algorithm for Fitting Implicit Polynomial Curves and Surfaces to Data
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2000
"... Of great importance to a wide variety of computer vision and image analysis problems is the ability to represent two (2D) and threedimensional (3D) data or objects. Implicit polynomial curves and surfaces are two of the most useful representations available. Their representational power is evidenc ..."
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Cited by 32 (4 self)
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Of great importance to a wide variety of computer vision and image analysis problems is the ability to represent two (2D) and threedimensional (3D) data or objects. Implicit polynomial curves and surfaces are two of the most useful representations available. Their representational power is evidenced by their ability to smooth noisy data and to interpolate through sparse or missing data. Furthermore, their associated Euclidean and affine invariants are powerful discriminators, making implicit polynomials a computationally attractive technology for recognizing objects in arbitrary positions with respect to cameras or range sensors. In this paper, we introduce a completely new approach to fitting implicit polynomials to data. The algorithm represents a significant advancement of implicit polynomial technology for three important reasons. First, it is orders of magnitude faster than existing methods. Second, it has significantly better repeatability and numerical stability than current m...