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This paper deals with the highly challenging problem of reconstructing the shape of a refracting object from a single image of its resulting caustic. Due to the ubiquity of transparent refracting objects in everyday life, reconstruction of…

Computer Vision and Pattern Recognition · Computer Science 2021-12-14 Marc Kassubeck , Moritz Kappel , Susana Castillo , Marcus Magnor

Structural damage detection using non-contact sensing remains a challenging problem in structural health monitoring. This study presents a data-driven framework based on Dynamic Mode Decomposition (DMD) for extracting structural dynamics…

Systems and Control · Electrical Eng. & Systems 2026-05-05 R K B M Rizmi , Shabbir Ahmed

We present a novel non-rigid reconstruction method using a moving RGB-D camera. Current approaches use only non-rigid part of the scene and completely ignore the rigid background. Non-rigid parts often lack sufficient geometric and…

Computer Vision and Pattern Recognition · Computer Science 2018-05-31 Shafeeq Elanattil , Peyman Moghadam , Sridha Sridharan , Clinton Fookes , Mark Cox

This paper presents an alternative approach to dehomogenisation of elastic Rank-N laminate structures based on the computer graphics discipline of phasor noise. The proposed methodology offers an improvement of existing methods, where…

Computational Engineering, Finance, and Science · Computer Science 2023-10-10 Rebekka V. Woldseth , J. Andreas Bærentzen , Ole Sigmund

Diffusion magnetic resonance imaging datasets suffer from low Signal-to-Noise Ratio, especially at high b-values. Acquiring data at high b-values contains relevant information and is now of great interest for microstructural and…

Computer Vision and Pattern Recognition · Computer Science 2016-06-27 Samuel St-Jean , Pierrick Coupé , Maxime Descoteaux

We propose MHR-Net, a novel method for recovering Non-Rigid Shapes from Motion (NRSfM). MHR-Net aims to find a set of reasonable reconstructions for a 2D view, and it also selects the most likely reconstruction from the set. To deal with…

Computer Vision and Pattern Recognition · Computer Science 2023-01-13 Haitian Zeng , Xin Yu , Jiaxu Miao , Yi Yang

The ability to extend the field of view of laparoscopy images can help the surgeons to obtain a better understanding of the anatomical context. However, due to tissue deformation, complex camera motion and significant three-dimensional (3D)…

Computer Vision and Pattern Recognition · Computer Science 2021-03-15 Haoyin Zhou , Jagadeesan Jayender

We contribute a dense SLAM system that takes a live stream of depth images as input and reconstructs non-rigid deforming scenes in real time, without templates or prior models. In contrast to existing approaches, we do not maintain any…

Computer Vision and Pattern Recognition · Computer Science 2019-05-01 Wei Gao , Russ Tedrake

Dynamic imaging involves the reconstruction of a spatio-temporal object at all times using its undersampled measurements. In particular, in dynamic computed tomography (dCT), only a single projection at one view angle is available at a…

Image and Video Processing · Electrical Eng. & Systems 2025-03-14 Berk Iskender , Sushan Nakarmi , Nitin Daphalapurkar , Marc L. Klasky , Yoram Bresler

In minimal invasive surgery, it is important to rebuild and visualize the latest deformed shape of soft-tissue surfaces to mitigate tissue damages. This paper proposes an innovative Simultaneous Localization and Mapping (SLAM) algorithm for…

Computer Vision and Pattern Recognition · Computer Science 2020-03-25 Jingwei Song , Jun Wang , Liang Zhao , Shoudong Huang , Gamini Dissanayake

Modeling complex rigid motion across large spatiotemporal spans remains an unresolved challenge in dynamic reconstruction. Existing paradigms are mainly confined to short-term, small-scale deformation and offer limited consideration for…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Yijun Xu , Jingrui Zhang , Yuhan Chen , Dingwen Wang , Lei Yu , Chu He

Recovering 3D structure and camera motion from images has been a long-standing focus of computer vision research and is known as Structure-from-Motion (SfM). Solutions to this problem are categorized into incremental and global approaches.…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Linfei Pan , Dániel Baráth , Marc Pollefeys , Johannes L. Schönberger

Dynamic Mode Decomposition (DMD) is a data-driven modal decomposition technique that extracts coherent spatio-temporal structures from high-dimensional time-series data. By decomposing the dynamics into a set of modes, each associated with…

Fluid Dynamics · Physics 2026-05-05 Yutaro Tanaka , Hiroya Nakao

Dynamic radiance field reconstruction methods aim to model the time-varying structure and appearance of a dynamic scene. Existing methods, however, assume that accurate camera poses can be reliably estimated by Structure from Motion (SfM)…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Yu-Lun Liu , Chen Gao , Andreas Meuleman , Hung-Yu Tseng , Ayush Saraf , Changil Kim , Yung-Yu Chuang , Johannes Kopf , Jia-Bin Huang

Magnetic Resonance Imaging (MRI) is highly susceptible to motion artifacts due to the extended acquisition times required for k-space sampling. These artifacts can compromise diagnostic utility, particularly for dynamic imaging. We propose…

Image and Video Processing · Electrical Eng. & Systems 2025-07-04 Frederic Wang , Jonathan I. Tamir

We demonstrate the use of shape-from-shading (SfS) to improve both the quality and the robustness of 3D reconstruction of dynamic objects captured by a single camera. Unlike previous approaches that made use of SfS as a post-processing…

Computer Vision and Pattern Recognition · Computer Science 2017-08-08 Qi Liu-Yin , Rui Yu , Lourdes Agapito , Andrew Fitzgibbon , Chris Russell

The large scale structure (LSS) of the universe is generated by the linear density gaussian modes, which are evolved into the observed nonlinear LSS. The posterior surface of the modes is convex in the linear regime, leading to a unique…

Cosmology and Nongalactic Astrophysics · Physics 2018-08-08 Yu Feng , Uros Seljak , Matias Zaldarriaga

In this paper, we show that the affine, non-rigid structure-from-motion problem can be solved by rank-one, thus degenerate, basis shapes. It is a natural reformulation of the classic low-rank method by Bregler et al., where it was assumed…

Computer Vision and Pattern Recognition · Computer Science 2019-05-01 Sami S. Brandt , Hanno Ackermann

We propose a new methodology to estimate the 3D displacement field of deformable objects from video sequences using standard monocular cameras. We solve in real time the complete (possibly visco-)hyperelasticity problem to properly describe…

Computer Vision and Pattern Recognition · Computer Science 2021-10-14 Alberto Badias , Iciar Alfaro , David Gonzalez , Francisco Chinesta , Elias Cueto

We propose a novel framework to learn the spatiotemporal variability in longitudinal 3D shape data sets, which contain observations of objects that evolve and deform over time. This problem is challenging since surfaces come with arbitrary…

Computer Vision and Pattern Recognition · Computer Science 2021-08-23 Hamid Laga , Marcel Padilla , Ian H. Jermyn , Sebastian Kurtek , Mohammed Bennamoun , Anuj Srivastava