Publications by Vincent Lepetit

A fast local descriptor for dense matching

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

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

Fast Non-Rigid Surface Detection, Registration and Realistic Augmentation

Pascal Fua, Vincent Lepetit, Julien Pilet

We present a real-time method for detecting deformable surfaces, with no need whatsoever for a priori pose knowledge. Our method starts from a set of wide baseline point matches between an undeformed image of the object and the image in which it is to be d ...

2008

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

Closed-Form Solution to Non-rigid 3D Surface Registration

Pascal Fua, Mathieu Salzmann, Vincent Lepetit

We present a closed-form solution to the problem of recovering the 3D shape of a non-rigid inelastic surface from 3D-to-2D correspondences. This lets us detect and reconstruct such a, surface by matching individual images against a reference configuration, ...

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

Pose Priors for Simultaneously Solving Alignment and Correspondence

Pascal Fua, Vincent Lepetit

Estimating a camera pose given a set of 3D-object and 2D-image feature points is a well understood problem when correspondences are given. However, when such correspondences cannot be established a priori, one must simultaneously compute them along with th ...

Springer2008

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

3D pose refinement from reflections

Pascal Fua, Mathieu Salzmann, Vincent Lepetit, Pascal Lagger

We demonstrate how to exploit reflections for accurate registration of shiny objects: The lighting environment can be retrieved from the reflections under a distant illumination assumption. Since it remains unchanged when the camera or the object of intere ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2008

Bridging the Gap between Detection and Tracking for 3D Monocular Video-Based Motion Capture

Pascal Fua, Vincent Lepetit, Andrea Fossati, Miodrag Dimitrijevic

We combine detection and tracking techniques to achieve robust 3-D motion recovery of people seen from arbitrary viewpoints by a single and potentially moving camera. We rely on detecting key postures, which can be done reliably, using a motion model to in ...

2007

Fast Keypoint Recognition in Ten Lines of Code

Pascal Fua, Vincent Lepetit, 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 ...

IEEE Xplore2007

Vincent Lepetit

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A fast local descriptor for dense matching

Keypoint Signatures for Fast Learning and Recognition

Fast Non-Rigid Surface Detection, Registration and Realistic Augmentation

Multiple 3D Object Tracking for Augmented Reality

Closed-Form Solution to Non-rigid 3D Surface Registration

Pose Priors for Simultaneously Solving Alignment and Correspondence

Keypoint Signatures for Fast Learning and Recognition

3D pose refinement from reflections

Bridging the Gap between Detection and Tracking for 3D Monocular Video-Based Motion Capture

Fast Keypoint Recognition in Ten Lines of Code

Keypoint Signatures for Fast Learning and Recognition

Multiple 3D Object Tracking for Augmented Reality

Closed-Form Solution to Non-rigid 3D Surface Registration

Fast Non-Rigid Surface Detection, Registration and Realistic Augmentation

A fast local descriptor for dense matching

3D pose refinement from reflections

Pose Priors for Simultaneously Solving Alignment and Correspondence

Keypoint Signatures for Fast Learning and Recognition

Bridging the Gap between Detection and Tracking for 3D Monocular Video-Based Motion Capture

Fast Keypoint Recognition in Ten Lines of Code