Publications associées à Speeded Up Robust Features

LDAHash: Improved Matching with Smaller Descriptors

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

Efficient Large Scale Multi-View Stereo for Ultra High Resolution Image Sets

Pascal Fua, Christoph Strecha, Engin Tola

We present a new approach for large scale multi-view stereo matching, which is designed to operate on ultra high resolution image sets and efficiently compute dense 3D point clouds. We show that, by using a robust descriptor for matching purposes and high ...

Springer Verlag2012

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

Fault Detection and Isolation in Multiple MEMS-IMUs Configurations

Jan Skaloud, Stéphane Guerrier

This research presents methods for detecting and isolating faults in multiple micro-electro-mechanical system inertial measurement unit (MEMS-IMU) configurations. First, geometric configurations with n sensor triads are investigated. It is proved that the ...

Institute of Electrical and Electronics Engineers2012

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

Alternative search techniques for face detection using location estimation and binary features

Venkatesh Bala Subburaman

The sliding window approach is the most widely used technique to detect objects from an image. In the past few years, classifiers have been improved in many ways to increase the scanning speed. Apart from the classifier design (such as the cascade), the sc ...

ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE2012

FREAK: Fast Retina Keypoint

Pierre Vandergheynst, Alexandre Massoud Alahi, Raphaël Ortiz

A large number of vision applications rely on matching keypoints across images. The last decade featured an arms-race towards faster and more robust keypoints and association algorithms: Scale Invariant Feature Transform (SIFT), Speed-up Robust Feature (SU ...

Ieee2012

On the Relevance of Sparsity for Image Classification

Pascal Fua, Engin Türetken, Vincent Lepetit, Germán González Serrano, Roberto Rigamonti, Matthew Brown, Fethallah Benmansour

In this paper we analyze empirically the importance of sparsifying representations for classification purposes. We focus on those obtained by convolving images with linear filters, which can be either hand designed or learned, and perform extensive experim ...

2012

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Speeded Up Robust Features

A Fast Parts-based Approach to Speaker Verification using Boosted Slice Classifiers

LDAHash: Improved Matching with Smaller Descriptors

Efficient Large Scale Multi-View Stereo for Ultra High Resolution Image Sets

Scale Invariant Features and Polar Descriptors in Omnidirectional Imaging

Fault Detection and Isolation in Multiple MEMS-IMUs Configurations

Learning Image Descriptors with the Boosting-Trick

Alternative Search Techniques for Face Detection Using Location Estimation and Binary Features

Alternative search techniques for face detection using location estimation and binary features

FREAK: Fast Retina Keypoint

On the Relevance of Sparsity for Image Classification

Graph Chatbot

Chattez avec Graph Search

On the Relevance of Sparsity for Image Classification

LDAHash: Improved Matching with Smaller Descriptors

A Fast Parts-based Approach to Speaker Verification using Boosted Slice Classifiers

Scale Invariant Features and Polar Descriptors in Omnidirectional Imaging

Efficient Large Scale Multi-View Stereo for Ultra High Resolution Image Sets

Learning Image Descriptors with the Boosting-Trick

Fault Detection and Isolation in Multiple MEMS-IMUs Configurations

Alternative search techniques for face detection using location estimation and binary features

Alternative Search Techniques for Face Detection Using Location Estimation and Binary Features

FREAK: Fast Retina Keypoint