中文
相关论文

相关论文: Non-iterative rigid 2D/3D point-set registration u…

200 篇论文

Non-rigid point cloud registration is a key component in many computer vision and computer graphics applications. The high complexity of the unknown non-rigid motion make this task a challenging problem. In this paper, we break down this…

计算机视觉与模式识别 · 计算机科学 2022-10-06 Yang Li , Tatsuya Harada

Correspondence problems are often modelled as quadratic optimization problems over permutations. Common scalable methods for approximating solutions of these NP-hard problems are the spectral relaxation for non-convex energies and the…

图形学 · 计算机科学 2017-05-18 Nadav Dym , Haggai Maron , Yaron Lipman

Pose estimation is a general problem in computer vision with wide applications. The relative orientation of a 3D reference object can be determined from a 3D rotated version of that object, or from a projection of the rotated object to a 2D…

计算机视觉与模式识别 · 计算机科学 2025-11-26 Andrew J. Hanson , Sonya M. Hanson

Parametric spatial transformation models have been successfully applied to image registration tasks. In such models, the transformation of interest is parameterized by a fixed set of basis functions as for example B-splines. Each basis…

计算机视觉与模式识别 · 计算机科学 2019-06-25 Robin Sandkühler , Simon Andermatt , Grzegorz Bauman , Sylvia Nyilas , Christoph Jud , Philippe C. Cattin

3D point cloud registration in remote sensing field has been greatly advanced by deep learning based methods, where the rigid transformation is either directly regressed from the two point clouds (correspondences-free approaches) or…

计算机视觉与模式识别 · 计算机科学 2022-03-25 Zhiyuan Zhang , Jiadai Sun , Yuchao Dai , Dingfu Zhou , Xibin Song , Mingyi He

Multiview point cloud registration is a fundamental task for constructing globally consistent 3D models. Existing approaches typically rely on feature extraction and data association across multiple point clouds; however, these processes…

计算机视觉与模式识别 · 计算机科学 2025-06-25 Yiran Zhou , Yingyu Wang , Shoudong Huang , Liang Zhao

Image registration and in particular deformable registration methods are pillars of medical imaging. Inspired by the recent advances in deep learning, we propose in this paper, a novel convolutional neural network architecture that couples…

With an aim to increase the capture range and accelerate the performance of state-of-the-art inter-subject and subject-to-template 3D registration, we propose deep learning-based methods that are trained to find the 3D position of…

计算机视觉与模式识别 · 计算机科学 2018-08-21 Seyed Sadegh Mohseni Salehi , Shadab Khan , Deniz Erdogmus , Ali Gholipour

We describe a diffeomorphic registration algorithm that allows groups of images to be accurately aligned to a common space, which we intend to incorporate into the SPM software. The idea is to perform inference in a probabilistic graphical…

计算机视觉与模式识别 · 计算机科学 2021-05-10 Mikael Brudfors , Yaël Balbastre , Guillaume Flandin , Parashkev Nachev , John Ashburner

We introduce fast randomized algorithms for solving semidefinite programming (SDP) relaxations of the partial permutation synchronization (PPS) problem, a core task in multi-image matching with significant relevance to 3D reconstruction.…

最优化与控制 · 数学 2025-06-26 Michael Lindsey , Yunpeng Shi

We present new large-scale algorithms for fitting a subgradient regularized multivariate convex regression function to $n$ samples in $d$ dimensions -- a key problem in shape constrained nonparametric regression with applications in…

最优化与控制 · 数学 2023-12-06 Wenyu Chen , Rahul Mazumder

The current bottleneck of globally solving mixed-integer (non-convex) quadratically constrained problem (MIQCP) is still to construct strong but computationally cheap convex relaxations, especially when dense quadratic functions are…

最优化与控制 · 数学 2014-03-24 Hongbo Dong

This paper presents a novel convex optimization-based method for finding the globally optimal solutions of a class of mixed-integer non-convex optimal control problems. We consider problems with non-convex constraints that restrict the…

最优化与控制 · 数学 2019-11-21 Danylo Malyuta , Behcet Acikmese

We propose a nonrigid registration approach for diffusion tensor images using a multicomponent information-theoretic measure. Explicit orientation optimization is enabled by incorporating tensor reorientation, which is necessary for…

计算机视觉与模式识别 · 计算机科学 2015-04-15 Mohammed Khader , A. Ben Hamza

Limited capture range, and the requirement to provide high quality initialization for optimization-based 2D/3D image registration methods, can significantly degrade the performance of 3D image reconstruction and motion compensation…

计算机视觉与模式识别 · 计算机科学 2018-01-24 Benjamin Hou , Bishesh Khanal , Amir Alansary , Steven McDonagh , Alice Davidson , Mary Rutherford , Jo V. Hajnal , Daniel Rueckert , Ben Glocker , Bernhard Kainz

Computerized registration between maxillofacial cone-beam computed tomography (CT) images and a scanned dental model is an essential prerequisite in surgical planning for dental implants or orthognathic surgery. We propose a novel method…

计算机视觉与模式识别 · 计算机科学 2021-01-26 Minyoung Chung , Jingyu Lee , Wisoo Song , Youngchan Song , Il-Hyung Yang , Jeongjin Lee , Yeong-Gil Shin

Commercial off the shelf (COTS) 3D scanners are capable of generating point clouds covering visible portions of a face with sub-millimeter accuracy at close range, but lack the coverage and specialized anatomic registration provided by more…

计算机视觉与模式识别 · 计算机科学 2017-08-18 Maxim Bazik , Daniel Crispell

3D alignment has become a very important part of 3D scanning technology. For instance, we can divide the alignment process into four steps: key point detection, key point description, initial pose estimation, and alignment refinement.…

计算机视觉与模式识别 · 计算机科学 2021-10-29 Abdenour Amamra , Khalid Boumaza

Blind Perspective-n-Point (PnP) is the problem of estimating the position and orientation of a camera relative to a scene, given 2D image points and 3D scene points, without prior knowledge of the 2D-3D correspondences. Solving for pose and…

计算机视觉与模式识别 · 计算机科学 2020-09-09 Dylan Campbell , Liu Liu , Stephen Gould

In solving hard computational problems, semidefinite program (SDP) relaxations often play an important role because they come with a guarantee of optimality. Here, we focus on a popular semidefinite relaxation of K-means clustering which…

机器学习 · 计算机科学 2018-09-07 Mariano Tepper , Anirvan M. Sengupta , Dmitri Chklovskii