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Learning Transformations To Reduce the Geometric Shift in Object Detection

Publications associées (51)

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Learning Pose Invariant and Covariant Classifiers from Image Sequences

Mustafa Özuysal

Object tracking and detection over a wide range of viewpoints is a long-standing problem in Computer Vision. Despite significant advance in wide-baseline sparse interest point matching and development of robust dense feature models, it remains a largely op ...

EPFL2010

Fast Keypoint Recognition using Random Ferns

Pascal Fua, Vincent Lepetit, Michael Calonder, Mustafa Özuysal

While feature point recognition is a key component of modern approaches to object detection, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. In this paper, we show that formulating the problem in ...

2010

Daisy: An Efficient Dense Descriptor Applied to Wide Baseline Stereo

Pascal Fua, Vincent Lepetit, Engin Tola

In this paper, we introduce a local image descriptor, DAISY, which is very efficient to compute densely. We also present an EM based algorithm to compute dense depth and occlusion maps from wide baseline image pairs using this descriptor. This yields much ...

Institute of Electrical and Electronics Engineers2010

Geometry-aware analysis of high-dimensional visual information sets

Effrosyni Kokiopoulou

Over the past few decades we have been experiencing a data explosion; massive amounts of data are increasingly collected and multimedia databases, such as YouTube and Flickr, are rapidly expanding. At the same time rapid technological advancements in mobil ...

EPFL2009

SECM for imaging and detection of latent fingerprints

Hubert Girault

Fingerprint analysis is one of the most important methods used for personal identification of evidence found at a crime scene for forensic purposes. Using scanning electrochemical microscopy (SECM) imaging, researchers can visualize the ultrastructure of h ...

2009

A Master-Slave Approach for Object Detection and Matching with Fixed and Mobile Cameras

Michel Bierlaire, Murat Kunt, Alexandre Massoud Alahi

Typical object detection algorithms on mobile cameras suffer from the lack of a-priori knowledge on the object to be detected. The variability in the shape, pose, color distribution, and behavior affect the robustness of the detection process. In general, ...

2008

Geometry-based scene representation with distributed vision sensors.

Pascal Frossard, Ivana Tosic

This paper addresses the problem of efficient representation and compression of scenes captured by distributed vision sensors. We propose a novel geometrical model to describe the correlation between different views of a three-dimensional scene. We first a ...

2007

Wyner-Ziv coding of multi-view omnidirectional images with overcomplete decompositions

Pascal Frossard, Ivana Tosic

This paper addresses the problem of distributed coding of light fields in camera networks. A novel distributed coding scheme with side information is presented, based on spherical image expansion over an overcomplete dictionary of geometric atoms. We propo ...

2007

Pattern Detection by Distributed Feature Extraction

Pascal Frossard, Effrosyni Kokiopoulou

This paper presents a distributed algorithm for the detection of patterns or their transformed versions, in noisy images. The proposed method projects the observed signal onto a redundant and structured dictionary of functions, which are distributed among ...

2006

Synthèse d'images moiré

Sylvain Chosson

We explore a new approach for synthesizing moiré images that can be used for authentication of documents. For synthesizing moiré images, we need two layers: a base layer made of replicated bands or parallelograms and a revealing layer made of transparent l ...

EPFL2006