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Fitting Egg-Shapes to Discretized Object Boundaries
This paper presents a novel method for fitting egg-shapes to discrete sets of boundary points. Egg-shapes extend ellipses by assigning a positive...
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Constrained least square progressive and iterative approximation (CLSPIA) for B-spline curve and surface fitting
Combining the Lagrange multiplier method, the Uzawa algorithm, and the least square progressive and iterative approximation (LSPIA), we proposed the co...
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Fitting and sharing multi-task learning
Multi-Task Learning is an effective method for learning cross-task knowledge. However, existing methods cannot fairly treat each task, their public...
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A family of hybrid iterative approximation methods for fitting blending curves
Data fitting is a fundamental research problem in many scientific fields. The progressive iterative approximation for least-squares fitting is an...
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Robust Heterogeneous Model Fitting for Multi-source Image Correspondences
Traditional feature detection and description methods, such as scale-invariant feature transform, are susceptible to nonlinear radiation distortions...
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Shape embedding and retrieval in multi-flow deformation
We propose a unified 3D flow framework for joint learning of shape embedding and deformation for different categories. Our goal is to recover shapes...
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Optimal Surface Fitting of Point Clouds Using Local Refinement Application to GIS Data
This open access book provides insights into the novel Locally Refined B-spline (LR B-spline) surface format, which is suited for representing...
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Unsupervised 3D Articulated Object Correspondences with Part Approximation and Shape Refinement
Reconstructing 3D human shapes with high-quality geometry as well as dense correspondences is important for many applications. Template fitting based...
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Concentric Ellipse Fitting with Bias Correction and Specialized Geometric-Based Clustering Approach
This paper addresses the problem of fitting concentric ellipses under general assumptions. We study two methods of obtaining an estimator of the...
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A strategy scheme of self-fitting based on gain adjustment for digital hearing aids
The widespread use of traditional digital hearing aids is limited to a certain extent due to the shortage of professionals, and the cumbersome...
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Imposing temporal consistency on deep monocular body shape and pose estimation
Accurate and temporally consistent modeling of human bodies is essential for a wide range of applications, including character animation,...
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Persistence B-spline grids: stable vector representation of persistence diagrams based on data fitting
Many attempts have been made in recent decades to integrate machine learning (ML) and topological data analysis. A prominent problem in applying...
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Forgery detection using polynomial fitting in recompressed JPEG images
Detection of double Joint photographic experts group (JPEG) compression is a major part of image forensics, especially double JPEG compression...
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BIDGCN: boundary-informed dynamic graph convolutional network for adaptive spline fitting of scattered data
Surface reconstruction from scattered point clouds is the process of generating surfaces from unstructured data configurations retrieved using an...
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3D Reconstruction of deformable linear objects based on cylindrical fitting
The manipulation of deformable linear objects (DLOs) is an important task in many fields, which raises demands for the perception of DLOs in real...
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Measurement of Solder Wetting Angle Based on Image Processing and Polynomial Fitting
The study focuses on the solder wetting image and proposes a solder wetting angle measurement method based on image processing and polynomial...
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Gradual Tensor Shape Checking
Tensor shape mismatch is a common source of bugs in deep learning programs. We propose a new type-based approach to detect tensor shape mismatches....
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A subdivision-based framework for shape reconstruction
Shape reconstruction from 3D point clouds is one of the most important topic in the field of computer graphics. In this paper, we propose a...
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CovidCurve: curve fitting modeling and early forecasting of the size and duration of Covid-19 outbreaks
The evolution of the cumulative number of infections, and the duration of Covid-19 outbreaks, are modeled and predicted, through a novel curve...
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Subsampling approach for least squares fitting of semi-parametric accelerated failure time models to massive survival data
Massive survival data are increasingly common in many research fields, and subsampling is a practical strategy for analyzing such data. Although...
