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Vincent Lepetit

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Related publications (76)

Page 1 of 4

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

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

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

Vision-Based Unmanned Aerial Vehicle Detection and Tracking for Sense and Avoid Systems

Krishna Raj Sapkota, Pascal Fua, Denis Gillet, Alcherio Martinoli, Vincent Lepetit, Steven Adriaan Roelofsen, Artem Rozantsev

We propose an approach for on-line detection of small Unmanned Aerial Vehicles (UAVs) and estimation of their relative positions and velocities in the 3D environment from a single moving camera in the context of sense and avoid systems. This problem is cha ...

Ieee2016

Keypoint Signatures for Fast Learning and Recognition

Pascal Fua, Vincent Lepetit, Michael Calonder

Statistical learning techniques have been used to dramatically speed-up keypoint matching by training a classifier to recognize a specific set of keypoints. However, the training itself is usually relatively slow and performed offline. Although methods hav ...

2008

A Novel Representation of Parts for Accurate 3D Object Detection and Tracking in Monocular Images

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

We present a method that estimates in real-time and under challenging conditions the 3D pose of a known object. Our method relies only on grayscale images since depth cameras fail on metallic objects; it can handle poorly textured objects, and cluttered, c ...

2015

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

An all-in-one solution to geometric and photometric calibration

Pascal Fua, Vincent Lepetit, Julien Pilet

We propose a fully automated approach to calibrating multiple cameras whose fields of view may not all overlap. Our technique only requires waving an arbitrary textured planar pattern in front of the cameras, which is the only manual intervention that is r ...

2006

EPnP: An Accurate O(n) Solution to the PnP Problem

Pascal Fua, Vincent Lepetit

We propose a non-iterative solution to the PnP problem-the estimation of the pose of a calibrated camera from n 3D-to-2D point correspondences-whose computational complexity grows linearly with n. This is in contrast to state-of-the-art methods that are O( ...

Springer Verlag2009

Structured Prediction of 3D Human Pose with Deep Neural Networks

Pascal Fua, Mathieu Salzmann, Vincent Lepetit, Bugra Tekin, Isinsu Katircioglu

Most recent approaches to monocular 3D pose estimation rely on Deep Learning. They either train a Convolutional Neural Network to directly regress from image to 3D pose, which ignores the dependencies between human joints, or model these dependencies via a ...

2016

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

Feature Harvesting for Tracking-by-Detection

Pascal Fua, François Fleuret, Vincent Lepetit, Mustafa Özuysal

We propose a fast approach to 3D object detection and pose estimation that owes its robustness to a training phase during which the target object slowly moves with respect to the camera. No additional information is provided to the system, save a very roug ...

Springer2006

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

Learning Image Descriptors with Boosting

Vincent Lepetit, Tomasz Piotr Trzcinski, Christos Marios Christoudias

We propose a novel and general framework to learn compact but highly discriminative floating-point and binary local feature descriptors. By leveraging the boosting-trick we first show how to efficiently train a compact floating-point descriptor that is ver ...

Institute of Electrical and Electronics Engineers2015

Appearance-based Keypoint Clustering

Pascal Fua, Sabine Süsstrunk, Vincent Lepetit

We present an algorithm for clustering sets of detected interest points into groups that correspond to visually distinct structure. Through the use of a suitable colour and texture representation, our clustering method is able to identify keypoints that be ...

2009

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

Pose Estimation for Category Specific Multiview Object Localization

Pascal Fua, Vincent Lepetit, Mustafa Özuysal

We propose an approach to overcome the two main challenges of 3D multiview object detection and localization: The variation of object features due to changes in the viewpoint and the variation in the size and aspect ratio of the object. Our approach procee ...

IEEE2009

Augmenting Deformable Objects in Real-Time

Pascal Fua, Vincent Lepetit, Julien Pilet

We present a real-time system that can draw virtual patterns or images on deforming real objects by estimating both the deformations and the shading parameters. We show that this is what is required to render the virtual elements so that they blend convinc ...

2005

Detecting Flying Objects using a Single Moving Camera

Pascal Fua, Vincent Lepetit, Artem Rozantsev

We propose an approach for detecting flying objects such as Unmanned Aerial Vehicles (UAVs) and aircrafts when they occupy a small portion of the field of view, possibly moving against complex backgrounds, and are filmed by a camera that itself moves. We a ...

2017

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

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

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