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Vincent Lepetit

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Publications associées (77)

Projection onto the Manifold of Elongated Structures for Accurate Extraction

Pascal Fua, Vincent Lepetit, Amos Sironi

Detection of elongated structures in 2D images and 3D image stacks is a critical prerequisite in many applications and Machine Learning-based approaches have recently been shown to deliver superior performance. However, these methods essentially classify i ...

2015

TILDE: A Temporally Invariant Learned DEtector

Pascal Fua, Vincent Lepetit, Yannick Verdie, Kwang Moo Yi

We introduce a learning-based approach to detect repeatable keypoints under drastic imaging changes of weather and lighting conditions to which state-of-the-art keypoint detectors are surprisingly sensitive. We first identify good keypoint candidates in mu ...

2015

On the Relevance of Sparsity for Image Classification

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

In this paper we empirically analyze 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 ...

Elsevier2014

Real-time landing place assessment in man-made environments

Pascal Fua, Vincent Lepetit, Xiaolu Sun, Christos Marios Christoudias

We propose a novel approach to the real-time landing site detection and assessment in unconstrained man-made environments using passive sensors. Because this task must be performed in a few seconds or less, existing methods are often limited to simple loca ...

Springer Verlag2014

Pose Estimation of Web-Shared Landscape Pictures

François Golay, Vincent Lepetit, Devis Tuia, Timothée Produit

We propose a robust method for registering high oblique images of landscapes. Typically, an input image can be registered by matching it against a set of registered images of the same location. While this has been shown to work very well for images of popu ...

2014

Multiscale Centerline Detection by Learning a Scale-Space Distance Transform

Pascal Fua, Vincent Lepetit, Amos Sironi

We propose a robust and accurate method to extract the centerlines and scale of tubular structures in 2D images and 3D volumes. Existing techniques rely either on filters designed to respond to ideal cylindrical structures, which lose accuracy when the lin ...

2014

Robust 3D Tracking with Descriptor Fields

Vincent Lepetit, Alberto Crivellaro

We introduce a method that can register challenging images from specular and poorly textured 3D environments, on which previous approaches fail. We assume that a small set of reference images of the environment and a partial 3D model are available. Like pr ...

2014

[DEMO] Tracking Texture-less, Shiny Objects with Descriptor Fields

Pascal Fua, Vincent Lepetit, Alberto Crivellaro, Yannick Verdie, Kwang Moo Yi

Our demo demonstrates the method we published at CVPR this year for tracking specular and poorly textured objects, and lets the visitors experiment with it and with their own patterns. Our approach only requires a standard monocular camera (no need for a d ...

2014

Learning Separable Filters

Pascal Fua, Vincent Lepetit, Roberto Rigamonti, Amos Sironi

2013

Boosting Binary Keypoint Descriptors

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

Binary keypoint descriptors provide an efficient alternative to their floating-point competitors as they enable faster processing while requiring less memory. In this paper, we propose a novel framework to learn an extremely compact binary descriptor we ca ...

2013

Supervised Feature Learning for Curvilinear Structure Segmentation

Pascal Fua, Vincent Lepetit, Roberto Rigamonti, Carlos Joaquin Becker

Springer2013

BRIEF: Computing a Local Binary Descriptor Very Fast

Pascal Fua, Vincent Lepetit, Mustafa Özuysal, Michael Calonder, Christoph Strecha, Tomasz Piotr Trzcinski

Binary descriptors are becoming increasingly popular as a means to compare feature points very fast and while requiring comparatively small amounts of memory. The typical approach to creating them is to first compute floating-point ones, using an algorithm ...

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

Gradient Response Maps for Real-Time Detection of Textureless Objects

Pascal Fua, Slobodan Ilic, Vincent Lepetit

We present a method for real-time 3D object instance detection that does not require a time-consuming training stage, and can handle untextured objects. At its core, our approach is a novel image representation for template matching designed to be robust t ...

Institute of Electrical and Electronics Engineers2012

Handling Motion-Blur in 3D Tracking and Rendering for Augmented Reality

Vincent Lepetit

The contribution of this paper is two-fold. First, we show how to extend the ESM algorithm to handle motion blur in 3D object tracking. ESM is a powerful algorithm for template matching-based tracking, but it can fail under motion blur. We introduce an ima ...

2012

Accurate and Efficient Linear Structure Segmentation by Leveraging Ad Hoc Features with Learned Filters

Vincent Lepetit, Roberto Rigamonti

Extracting linear structures, such as blood vessels or dendrites, from images is crucial in many medical imagery applications, and many handcrafted features have been proposed to solve this problem. However, such features rely on assumptions that are never ...

Springer2012

Thick Boundaries in Binary Space and Their Influence on Nearest-Neighbor Search

Pascal Fua, Vincent Lepetit, Tomasz Piotr Trzcinski

Binary descriptors allow faster similarity computation than real-valued ones while requiring much less storage. As a result, many algorithms have recently been proposed to binarize ﬂoating-point descriptors so that they can be searched for quickly. Unfortu ...

Elsevier2012

Real-time interactive modeling and scalable multiple object tracking for AR

Vincent Lepetit

We propose a real-time solution for modeling and tracking multiple 3D objects in unknown environments for Augmented Reality. The proposed solution consists of both scalable tracking and interactive modeling. Our contribution is twofold: First, we show how ...

Pergamon-Elsevier Science Ltd2012

Are Sparse Representations Really Relevant for Image Classification?

Vincent Lepetit, Roberto Rigamonti, Matthew Brown

Recent years have seen an increasing interest in sparse representations for image classiﬁcation and object recognition, probably motivated by evidence from the analysis of the primate visual cortex. It is still unclear, however, whether or not sparsity hel ...

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

Turning Augmented Reality into a media: Design exploration to build a dedicated visual language

Pascal Fua, Nicolas Henchoz, Vincent Lepetit

This work collects the explorations conducted within the EPFL+ECAL Lab by several designers to interpret the various spheres of action of Augmented Reality in order to derive visual principles. These principles seek to contribute to developing a specific v ...

IEEE2011

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