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

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Sparse Iterative Closest Point

Mark Pauly, Sofien Bouaziz, 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 ...

Wiley-Blackwell2013

Multichannel Blind Deconvolution Using Low-rank and Sparse Decomposition

Pierre Vandergheynst, Mahdad Hosseini Kamal

Multiple images of the same scene improve the result of multichannel blind deconvolution problem. However, existing techniques require alignment of channels. We define a multichannel deconvolution scheme for highly correlated images to estimated the blur k ...

2013

3-D Head Tracking via Invariant Keypoint Learning

Haoqi Wang, Vincent Lepetit

Keypoint matching is a standard tool to solve the correspondence problem in vision applications. However, in 3-D face tracking, this approach is often deficient because the human face complexities, together with its rich viewpoint, nonrigid expression, and ...

Ieee-Inst Electrical Electronics Engineers Inc2012

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

LDAHash: Improved Matching with Smaller Descriptors

Pascal Fua, Christoph Strecha

SIFT-like local feature descriptors are ubiquitously employed in computer vision applications such as content-based retrieval, video analysis, copy detection, object recognition, photo tourism, and 3D reconstruction. Feature descriptors can be designed to ...

Institute of Electrical and Electronics Engineers2012

Scale Invariant Features and Polar Descriptors in Omnidirectional Imaging

Pascal Frossard, Zafer Arican

We propose a method to compute scale invariant features in omnidirectional images. We present a formulation based on Riemannian geometry for the definition of differential operators on non-Euclidian manifolds that describe the mirror and lens structure in ...

Institute of Electrical and Electronics Engineers2012

Alignment of uncalibrated images for multi-view classification

Pascal Frossard, Elif Vural, Ömer Sercan Arik

Efficient solutions for the classification of multi-view images can be built on graph-based algorithms when little information is known about the scene or cameras. Such methods typically require a pairwise similarity measure between images, where a common ...

2011

Multispectral Interest Points for RGB-NIR Image Registration

Sabine Süsstrunk, Matthew Brown, Damien Firmenich

This paper explores the use of joint colour and near-infrared (NIR) information for feature based matching and image registration. In particular, we investigate multispectral generalisations of two popular interest point detectors (Harris and difference of ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

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

Graph Chatbot

Chattez avec Graph Search

Sparse Iterative Closest Point

Sparse Binary Features for Image Classification

Multichannel Blind Deconvolution Using Low-rank and Sparse Decomposition

Analysis of Descent-Based Image Registration

3-D Head Tracking via Invariant Keypoint Learning

Learning Image Descriptors with the Boosting-Trick

LDAHash: Improved Matching with Smaller Descriptors

Scale Invariant Features and Polar Descriptors in Omnidirectional Imaging

Alignment of uncalibrated images for multi-view classification

Multispectral Interest Points for RGB-NIR Image Registration

Alignment of uncalibrated images for multi-view classification

Sparse Iterative Closest Point

Sparse Binary Features for Image Classification

Multichannel Blind Deconvolution Using Low-rank and Sparse Decomposition

Analysis of Descent-Based Image Registration

Learning Image Descriptors with the Boosting-Trick

3-D Head Tracking via Invariant Keypoint Learning

LDAHash: Improved Matching with Smaller Descriptors

Scale Invariant Features and Polar Descriptors in Omnidirectional Imaging

Multispectral Interest Points for RGB-NIR Image Registration