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François Fleuret

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Related publications (315)

Tracking Multiple People under Global Appearance Constraints

Pascal Fua, Jérôme Berclaz, François Fleuret, Horesh Beny Ben Shitrit

In this paper, we show that tracking multiple people whose paths may intersect can be formulated as a convex global optimization problem. Our proposed framework is designed to exploit image appearance cues to prevent identity switches. Our method is effect ...

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

FlowBoost - Appearance Learning from Sparsely Annotated Video

David Hasler, François Fleuret, Karim Ali

We propose a new learning method which exploits temporal consistency to successfully learn a complex appearance model from a sparsely labeled training video. Our approach consists in iteratively improving an appearance based model built with a Boosting pro ...

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

Multiple Object Tracking using K-Shortest Paths Optimization

Pascal Fua, Jérôme Berclaz, François Fleuret, Engin Türetken

Multi-object tracking can be achieved by detecting objects in individual frames and then linking detections across frames. Such an approach can be made very robust to the occasional detection failure: If an object is not detected in a frame but is in previ ...

Institute of Electrical and Electronics Engineers2011

Delineating Trees in Noisy 2D Images and 3D Image Stacks

Pascal Fua, François Fleuret, Germán González Serrano, Engin Türetken

We present a novel approach to fully automated delineation of tree structures in noisy 2D images and 3D image stacks. Unlike earlier methods that rely mostly on local evidence, our method builds a set of candidate trees over many different subsets of point ...

2010

Multi-layer Boosting for Pattern Recognition

François Fleuret

We extend the standard boosting procedure to train a two-layer classifier dedicated to handwritten char- acter recognition. The scheme we propose relies on a hidden layer which extracts feature vectors on a fixed number of points of interest, and an output ...

2009

Classification-based Probabilistic Modeling of Texture Transition for Fast Line Search Tracking and Delineation

Pascal Fua, Seyed Ali Shahrokni, François Fleuret

We introduce a classification-based approach to finding occluding texture boundaries. The classifier is composed of a set of weak lear ners which operate on image intensity discriminative features which are defined on small patches and fast to compute. A d ...

Institute of Electrical and Electronics Engineers2009

Joint Pose Estimator and Feature Learning for Object Detection

David Hasler, Pascal Fua, François Fleuret, Karim Ali

A new learning strategy for object detection is presented. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform ba ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

Stationary Features and Cat Detection

François Fleuret

Most discriminative techniques for detecting instances from object categories in still images consist of looping over a partition of a pose space with dedicated binary classifiers. The efficiency of this strategy for a complex pose, i.e., for fine-grained ...

2008

Multi-Camera People Tracking with a Probabilistic Occupancy Map

Pascal Fua, Jérôme Berclaz, François Fleuret

Given two to four synchronized video streams taken at eye level and from different angles, we show that we can effectively combine a generative model with dynamic programming to accurately follow up to six individuals across thousands of frames in spite of ...

Institute of Electrical and Electronics Engineers2008

Automated Delineation of Dendritic Networks in Noisy Image Stacks

Pascal Fua, François Fleuret, Germán González Serrano

We present a novel approach to 3D delineation of dendritic networks in noisy image stacks. We achieve a level of automation beyond that of state-of-the-art systems, which model dendrites as continuous tubular structures and postulate simple appearance mode ...

Springer-Verlag2008

Principled Detection-by-Classification from Multiple Views

Pascal Fua, Jérôme Berclaz, François Fleuret

Machine-learning based classification techniques have been shown to be effective at detecting objects in complex scenes. However, the final results are often obtained from the alarms produced by the classifiers through a post-processing which typically rel ...

2008

Automated Delineation of Dendritic Networks in Noisy Image Stacks

Pascal Fua, François Fleuret, Germán González Serrano

2008

Robust Multi-View Change Detection

Pascal Fua, Jérôme Berclaz, François Fleuret, Alessandro Lanza

We present a multi-view change detection approach aimed at being robust with respect to common “disturbance factors” yielding image changes in realworld applications. Disturbance factors causing “slow” or “fast-and-global” image variations, such as light c ...

2007

Robust People Tracking with Global Trajectory Optimization

Pascal Fua, Jérôme Berclaz, François Fleuret

Given three or four synchronized videos taken at eye level and from different angles, we show that we can effectively use dynamic programming to accurately follow up to six individuals across thousands of frames in spite of significant occlusions. In addit ...

2006

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

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