Results 261 to 270 of about 1,349,497 (315)
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DIFFERENTIAL SHAPE STATISTICAL ANALYSIS
International Journal of Wavelets, Multiresolution and Information Processing, 2007A novel statistical approach that involves differential shape is proposed to analyze contour segments. First, a moment-based algorithm to represent the differential contour segment in an efficient way is introduced. Then, a curvature mean-shift method is adopted to search for the salient features.
Chen, Yufeng +3 more
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2021
The chapter describes stochastic models of shapes from a Hamiltonian viewpoint, including Langevin models, Riemannian Brownian motions and stochastic variational systems. Starting from the deterministic setting of outer metrics on shape spaces and transformation groups, we discuss recent approaches to introducing noise in shape analysis from a physical
Arnaudon, Alexis +2 more
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The chapter describes stochastic models of shapes from a Hamiltonian viewpoint, including Langevin models, Riemannian Brownian motions and stochastic variational systems. Starting from the deterministic setting of outer metrics on shape spaces and transformation groups, we discuss recent approaches to introducing noise in shape analysis from a physical
Arnaudon, Alexis +2 more
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Fourier Analysis of Cephalometric Shapes
The Cleft Palate-Craniofacial Journal, 1996Craniofacial growth and development involve both size and shape variations. Shape variations can be assessed independently from size using mathematical methods such as the Fourier series. A method for the reconstruction of outlines starting from selected landmarks and for their Fourier analysis has been developed and applied to analyze the age ...
V.F. Ferrario +4 more
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SHAPE MODELING AND SHAPE ANALYSIS BASED ON SINGULARITIES
International Journal of Shape Modeling, 1996Summary: To analyze given object shapes, it is necessary first to model the shapes and then to analyze the models. This paper proposes a method of modeling and analyzing two-dimensional (2D) and three-dimensional (3D) shapes based on singularities. First, a function is defined on an object.
Shinagawa, Yoshihisa +3 more
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Three-Dimensional Shape Analysis Using Local Shape Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1981The three-dimensional shape analysis problem is a very demanding test of shape analysis algorithms. Previous approaches to the problem have employed global features such as moments and Fourier descriptors. Global features lack the capacity for solving the partial shape recognition problem, in which only part of the unknown shape is available.
T P, Wallace, O R, Mitchell, K, Fukunaga
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Shape Analysis and Structuring
2008Several techniques have been developed in the literature for processing different aspects of the geometry of shapes, for representing and manipulating a shape at different levels of detail, and for describing a shape at a structural level as a concise, part-based, or iconic model.
DE FLORIANI, LEILA, M. SPAGNUOLO
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Journal of Computational and Graphical Statistics, 1999
Abstract Emulating human vision, computer vision systems aim to recognize object shape from images. The main difficulty in recognizing objects from images is that the shape depends on the viewpoint. This difficulty can be resolved by using projective invariants to describe the shape.
Colin R. Goodall, Kanti V. Mardia
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Abstract Emulating human vision, computer vision systems aim to recognize object shape from images. The main difficulty in recognizing objects from images is that the shape depends on the viewpoint. This difficulty can be resolved by using projective invariants to describe the shape.
Colin R. Goodall, Kanti V. Mardia
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2D-Shape Analysis Using Shape Invariants
Applied Mechanics and Materials, 2014High efficiency detection of two-dimensional objects is achieved by an appropriate choice of object invariants. The aim is to show an example of the construction of an algorithm for rapid identification also for highly complex objects. The program structure works in a similar way as animal systems in nature.
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2017
We present a data-driven verification framework to automatically prove memory safety of heap-manipulating programs. Our core contribution is a novel statistical machine learning technique that maps observed program states to (possibly disjunctive) separation logic formulas describing the invariant shape of (possibly nested) data structures at relevant ...
Marc Brockschmidt +4 more
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We present a data-driven verification framework to automatically prove memory safety of heap-manipulating programs. Our core contribution is a novel statistical machine learning technique that maps observed program states to (possibly disjunctive) separation logic formulas describing the invariant shape of (possibly nested) data structures at relevant ...
Marc Brockschmidt +4 more
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2016
Using the methods and models described in the previous chapters, we present the results of the shape optimization of the capsule vehicle in this chapter. We start by discussing the results of a Monte Carlo analysis of the search space, from which we draw preliminary conclusions on the influence of the various contraint functions.
Dominic Dirkx, Erwin Mooij
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Using the methods and models described in the previous chapters, we present the results of the shape optimization of the capsule vehicle in this chapter. We start by discussing the results of a Monte Carlo analysis of the search space, from which we draw preliminary conclusions on the influence of the various contraint functions.
Dominic Dirkx, Erwin Mooij
openaire +1 more source