paper-with-me

홈 › Papers

IRA: A shape matching approach for recognition and comparison of generic atomic patterns

2021-10-29 · Miha Gunde, Nicolas Salles, Anne Hémeryck, Layla Martin-Samos

We propose a versatile, parameter-less approach for solving the shape matching problem, specifically in the context of atomic structures when atomic assignments are not known a priori. The algorithm Iteratively suggests Rotated atom-centered reference frames and Assignments (Iterative Rotations and Assignments, IRA). The frame for which a permutationally invariant set-set distance, namely the Hausdorff distance, returns minimal value is chosen as the solution of the matching problem. IRA is able to find rigid rotations, reflections, translations, and permutations between structures with different numbers of atoms, for any atomic arrangement and pattern, periodic or not. When distortions are present between the structures, optimal rotation and translation are found by further applying a standard Singular Value Decomposition-based method. To compute the atomic assignments under the one-to-one assignment constraint, we develop our own algorithm, Constrained Shortest Distance Assignments (CShDA). The overall approach is extensively tested on several structures, including distorted structural fragments. Efficiency of the proposed algorithm is shown as a benchmark comparison against two other shape matching algorithms. We discuss the use of our approach for the identification and comparison of structures and structural fragments through two examples: a replica exchange trajectory of a cyanine molecule, in which we show how our approach could aid the exploration of relevant collective coordinates for clustering the data; and an SiO$_2$ amorphous model, in which we compute distortion scores and compare them with a classical strain-based potential. The source code and benchmark data are available at \url{https://github.com/mammasmias/IterativeRotationsAssignments}.

📄 PDF Abstract BibTeX arXiv:2111.00939

Code (1)

mammasmias/iterativerotationsassignments 공식 구현

Similar Papers 제목 키워드 기반

A Random-Fern based Feature Approach for Image Matching

2017-06-04 · Yong Khoo, Seo-hyeon Keun

Image or object recognition is an important task in computer vision. With the hight-speed processing power on modern platforms and the availability of mobile phones everywhere, millions of photos are uploaded to the inte…

General ClassificationInformation RetrievalObject RecognitionRetrieval

Hand-Shadow Poser

2025-05-11 · Hao Xu, Yinqiao Wang, Niloy J. Mitra, Shuaicheng Liu 외

Hand shadow art is a captivating art form, creatively using hand shadows to reproduce expressive shapes on the wall. In this work, we study an inverse problem: given a target shape, find the poses of left and right hands…

BOTM: Echocardiography Segmentation via Bi-directional Optimal Token Matching

2025-05-23 · Zhihua Liu, Lei Tong, Xilin He, Che Liu 외

Existed echocardiography segmentation methods often suffer from anatomical inconsistency challenge caused by shape variation, partial observation and region ambiguity with similar intensity across 2D echocardiographic se…

AnatomySegmentation

On Matching Faces with Alterations due to Plastic Surgery and Disguise

2018-11-18 · Saksham Suri, Anush Sankaran, Mayank Vatsa, Richa Singh

Plastic surgery and disguise variations are two of the most challenging co-variates of face recognition. The state-of-art deep learning models are not sufficiently successful due to the availability of limited training s…

Face Recognition

ShapeY: Measuring Shape Recognition Capacity Using Nearest Neighbor Matching

2021-11-16 · NeurIPS Workshop ImageNet_PPF 2021 12 · Jong Woo Nam, Amanda S. Rios, Bartlett W. Mel

Object recognition in humans depends primarily on shape cues. We have developed a new approach to measuring the shape recognition performance of a vision system based on nearest neighbor view matching within the system's…

ObjectObject Recognition