Publications associées à Registration with the Point Cloud Library A Modular Framework for Aligning in 3-D

Aggregating Spatial and Photometric Context for Photometric Stereo

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

EPFL2024

Robust Isometric Non-Rigid Structure-From-Motion

Shaifali Parashar

Non-Rigid Structure-from-Motion (NRSfM) reconstructs a deformable 3D object from keypoint correspondences established between monocular 2D images. Current NRSfM methods lack statistical robustness, which is the ability to cope with correspondence errors. T ...

IEEE COMPUTER SOC2022

Chemiscope: interactive structure-property explorer for materials and molecules

Michele Ceriotti, Guillaume André Jean Fraux

The number of materials or molecules that can be created by combining different chemical elements in various proportions and spatial arrangements is enormous. Computational chemistry can be used to generate databases containing billions of potential struct ...

2020

Reconciling Matching Networks of Conceptual Models

Karl Aberer, Quoc Viet Hung Nguyen, Zoltán Miklós, Thành Tâm Nguyên

Conceptual models such as database schemas, ontologies or process models have been established as a means for effective engineering of information systems. Yet, for complex systems, conceptual models are created by a variety of stakeholders, which calls fo ...

2019

Achieving high-resolution thermal imagery in low-contrast lake surface waters by aerial remote sensing and image registration

Ulrich Lemmin, Daniel Sage, David Andrew Barry, Abolfazl Irani Rahaghi

A two-platform measurement system for realizing airborne thermography of the Lake Surface Water Temperature (LSWT) with ~0.8 m pixel resolution (sub-pixel satellite scale) is presented. It consists of a tethered Balloon Launched Imaging and Monitoring Plat ...

2019

Semantic Attribute Matching Networks

Seungryong Kim

We present semantic attribute matching networks (SAM-Net) for jointly establishing correspondences and transferring attributes across semantically similar images, which intelligently weaves the advantages of the two tasks while overcoming their limitations ...

IEEE2019

Eigendecomposition-free Training of Deep Networks with Zero Eigenvalue-based Losses

Pascal Fua, Mathieu Salzmann, Fei Wang, Kwang Moo Yi, Zheng Dang, Yinlin Hu

Many classical Computer Vision problems, such as essential matrix computation and pose estimation from 3D to 2D correspondences, can be solved by ﬁnding the eigenvector corresponding to the smallest, or zero, eigenvalue of a matrix representing a linear sy ...

2018

HD-Index: Pushing the Scalability-Accuracy Boundary for Approximate kNN Search in High-Dimensional Spaces

Arnab Bhattacharya, Akhil Arora, Piyush Kumar

Nearest neighbor searching of large databases in high-dimensional spaces is inherently difficult due to the curse of dimensionality. A flavor of approximation is, therefore, necessary to practically solve the problem of nearest neighbor search. In this pap ...

ASSOC COMPUTING MACHINERY2018

Towards Scalable Segmentation of 3D Image Stacks

Carlos Joaquin Becker

Imaging modalities such as Electron Microscopy (EM) and Light Microscopy (LM) can now deliver high-quality, high-resolution image stacks of neural structures. Though these imaging modalities can be used to analyze a variety of components that are critical ...

EPFL2016

Learning to Match Aerial Images with Deep Attentive Architectures

Pascal Fua, Eduard Trulls Fortuny, Hani Altwaijry

Image matching is a fundamental problem in Computer Vision. In the context of feature-based matching, SIFT and its variants have long excelled in a wide array of applications. However, for ultra-wide baselines, as in the case of aerial images captured unde ...

2016

Domain Adaptation for Microscopy Imaging

Pascal Fua, Christos Marios Christoudias, Carlos Joaquin Becker

Electron and Light Microscopy imaging can now deliver high-quality image stacks of neural structures. However, the amount of human annotation effort required to analyze them remains a major bottleneck. While Machine Learning algorithms can be used to help ...

Institute of Electrical and Electronics Engineers2015

Signal structure: from manifolds to molecules and structured sparsity

Sofia Karygianni

Effective representation methods and proper signal priors are crucial in most signal processing applications. In this thesis we focus on different structured models and we design appropriate schemes that allow the discovery of low dimensional latent struct ...

EPFL2015

Non-Rigid Graph Registration using Active Testing Search

Pascal Fua, Jan Kybic, Raphael Sznitman, Miguel Amável Dos Santos Pinheiro

We present a new approach for matching sets of branching curvilinear structures that form graphs embedded in R2 or R3 and may be subject to deformations. Unlike earlier methods, ours does not rely on local appearance similarity nor does require a good init ...

Institute of Electrical and Electronics Engineers2015

Analysis of Image Registration with Tangent Distance

Pascal Frossard, Elif Vural

The computation of the geometric transformation between a reference and a target image, known as image registration or alignment, corresponds to the projection of the target image onto the transformation manifold of the reference image (the set of images g ...

2014

Coupled Structure-from-Motion and 3D Symmetry Detection for Urban Facades

Duygu Ceylan, Mark Pauly

Repeated structures are ubiquitous in urban facades. Such repetitions lead to ambiguity in establishing correspondences across sets of unordered images. A decoupled structure-from-motion reconstruction followed by symmetry detection often produces errors: ...

2014

Recovering Badly Exposed Objects From Digital Photos Using Internet Images

Stefan Winkler, Sabine Süsstrunk

In this paper we consider the problem of clipped-pixel recovery over an entire badly exposed image region, using two correctly exposed images of the scene that may be captured under different conditions. The first reference image is used to recover texture ...

2014

Sparse Iterative Closest Point

Sofien Bouaziz, Mark Pauly, Andrea Tagliasacchi

Rigid registration of two geometric data sets is essential in many applications, including robot navigation, surface reconstruction, and shape matching. Most commonly, variants of the Iterative Closest Point (ICP) algorithm are employed for this task. Thes ...

2013

Analysis of Descent-Based Image Registration

Pascal Frossard, Elif Vural

We present a performance analysis for image registration with gradient descent. We consider a typical multiscale registration setting where the global 2-D translation between a pair of images is estimated by smoothing the images and minimizing the distance ...

2013

Transformation-Invariant Analysis of Visual Signals with Parametric Models

Elif Vural

The analysis of collections of visual data, e.g., their classification, modeling and clustering, has become a problem of high importance in a variety of applications. Meanwhile, image data captured in uncontrolled environments by arbitrary users is very li ...

EPFL2013

Learning Image Descriptors with the Boosting-Trick

Pascal Fua, Vincent Lepetit, Tomasz Piotr Trzcinski, Christos Marios Christoudias

In this paper we apply boosting to learn complex non-linear local visual feature representations, drawing inspiration from its successful application to visual object detection. The main goal of local feature descriptors is to distinctively repre- sent a s ...

2012