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Vincent Lepetit

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Related publications (76)

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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

ESM-Blur: Handling and Rendering Blur in 3D Tracking and Augmentation

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 track- ing. ESM is a powerful algorithm for template matching-based tracking, but it can fail under motion blur. We introduce an i ...

2009

Retexturing in the Presence of Complex Illumination and Occlusions

Pascal Fua, Vincent Lepetit, Julien Pilet

We present a non-rigid registration technique that achieves spatial, photometric, and visibility accuracy. It lets us photo-realistically augment 3D deformable surfaces under complex illumination conditions and in spite of severe occlusions. There are many ...

2007

A fast local descriptor for dense matching

Pascal Fua, Vincent Lepetit, Engin Tola

We introduce a novel local image descriptor designed for dense wide-baseline matching purposes. We feed our descriptors to a graph-cuts based dense depth map estimation algorithm and this yields better wide-baseline performance than the commonly used corre ...

2008

Human body pose detection using Bayesian spatio-temporal templates

Pascal Fua, Vincent Lepetit

We present a template-based approach to detecting human silhouettes in a specific walking pose. Our templates consist of short sequences of 2D silhouettes obtained from motion capture data. This lets us incorporate motion information into them and helps di ...

Elsevier2006

Pose Estimation of Web-Shared Landscape Pictures

Devis Tuia, Vincent Lepetit, François Golay, 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

Multiple 3D Object Tracking for Augmented Reality

Vincent Lepetit

We present a method that is able to track several 3D objects si- multaneously, robustly, and accurately in real-time. While many applications need to consider more than one object in practice, the existing methods for single object tracking do not scale we ...

2008

Learning to Find Good Correspondences

Pascal Fua, Mathieu Salzmann, Vincent Lepetit, Kwang Moo Yi, Eduard Trulls Fortuny

We develop a deep architecture to learn to find good correspondences for wide-baseline stereo. Given a set of putative sparse matches and the camera intrinsics, we train our network in an end-to-end fashion to label the correspondences as inliers or outlie ...

2018

Learning to Assign Orientations to Feature Points

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

We show how to train a Convolutional Neural Network to assign a canonical orientation to feature points given an image patch centered on the feature point. Our method improves feature point matching upon the state-of-the art and can be used in conjunction ...

2016

Method, system, and device for learned invariant feature transform for computer images

Pascal Fua, Vincent Lepetit, Kwang Moo Yi, Eduard Trulls Fortuny

A method for training a feature detector of an image processing device, including the steps of detecting features in the image to generate a score map, computing a center of mass on the score map to generate a location, extracting a patch from the image at ...

2018

TILDE: A Temporally Invariant Learned DEtector

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

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

Learning Lightprobes for Mixed Reality Illumination

Pascal Fua, Vincent Lepetit, Kwang Moo Yi

This paper presents the first photometric registration pipeline for Mixed Reality based on high quality illumination estimation by convolutional neural network (CNN) methods. For easy adaptation and deployment of the system, we train the CNN using purely s ...

2017

Multiscale Centerline Detection

Pascal Fua, Vincent Lepetit, Engin Türetken, Amos Sironi

Finding the centerline and estimating the radius of linear structures is a critical first step in many applications, ranging from road delineation in 2D aerial images to modeling blood vessels, lung bronchi, and dendritic arbors in 3D biomedical image stac ...

Institute of Electrical and Electronics Engineers2016

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 ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2008

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

Pascal Fua, Vincent Lepetit, Nicolas Henchoz

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

General Constraints for Batch Multiple-Target Tracking Applied to Large-Scale Videomicroscopy

Vincent Lepetit, Kevin Smith

While there is a large class of Multiple-Target Tracking (MTT) problems for which batch processing is possible and desirable, batch MTT remains relatively unexplored in comparison to sequential approaches. In this paper, we give a principled probabilistic ...

IEEE2008

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

Keypoint Recognition using Randomized Trees

Pascal Fua, Vincent Lepetit

In many 3--D object-detection and pose-estimation problems, run-time performance is of critical importance. However, there usually is time to train the system, which we will show to be very useful. Assuming that several registered images of the target obje ...

2006

Learning Separable Filters

Pascal Fua, Vincent Lepetit, Bugra Tekin, Roberto Rigamonti, Amos Sironi

Learning filters to produce sparse image representations in terms of overcomplete dictionaries has emerged as a powerful way to create image features for many different purposes. Unfortunately, these filters are usually both numerous and non-separable, mak ...

Ieee Computer Soc2015

Accurate Non-Iterative 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 method that are ...

2007