References of "Piater, Justus"
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See detailReinforcement Learning of Perceptual Classes using Q Learning Updates
Jodogne, Sébastien ULg; Piater, Justus ULg

in Proc. of the 23rd IASTED International Conference on Artificial Intelligence and Applications (2005)

Detailed reference viewed: 8 (4 ULg)
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See detailA Modular Multi-camera Framework for Team Sport Tracking
Hayet, Jean-Bernard; Mathes, Thomas; Czyz, Jacek et al

Conference (2005)

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See detailObject tracking using a combined appearance and geometric model
Gabriel, Pierre; Piater, Justus ULg; Verly, Jacques ULg

in HF Journal -- Belgian Journal of Electronics Communications (2005), (1), 46

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See detailRandom Subwindows for Robust Image Classification
Marée, Raphaël ULg; Geurts, Pierre ULg; Piater, Justus ULg et al

in Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2005) (2005)

We present a novel, generic image classification method based on a recent machine learning algorithm (ensembles of extremely randomized decision trees). Images are classified using randomly extracted ... [more ▼]

We present a novel, generic image classification method based on a recent machine learning algorithm (ensembles of extremely randomized decision trees). Images are classified using randomly extracted subwindows that are suitably normalized to yield robustness to certain image transformations. Our method is evaluated on four very different, publicly available datasets (COIL-100, ZuBuD, ETH-80, WANG). Our results show that our automatic approach is generic and robust to illumination, scale, and viewpoint changes. An extension of the method is proposed to improve its robustness with respect to rotation changes. [less ▲]

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See detailDecision Trees and Random Subwindows for Object Recognition
Marée, Raphaël ULg; Geurts, Pierre ULg; Piater, Justus ULg et al

in ICML workshop on Machine Learning Techniques for Processing Multimedia Content (MLMM2005) (2005)

In this paper, we compare five tree-based machine learning methods within a recent generic image classification framework based on random extraction and classification of subwindows. We evaluate them on ... [more ▼]

In this paper, we compare five tree-based machine learning methods within a recent generic image classification framework based on random extraction and classification of subwindows. We evaluate them on three publicly available object recognition datasets (COIL-100, ETH-80, and ZuBuD). Our comparison shows that this general and conceptually simple framework yields good results when combined with ensemble of decision trees, especially when using Tree Boosting or Extra-Trees. The latter is also particularly attractive in terms of computational efficiency. [less ▲]

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See detailTracking by cluster analysis of feature points and multiple particle filters
Du, Wei ULg; Piater, Justus ULg

in Pattern Recognition and Image Analysis (2005)

A moving target produces a coherent cluster of feature points in the image plane. This motivates our novel method of tracking multiple targets by cluster analysis of feature points and Multiple particle ... [more ▼]

A moving target produces a coherent cluster of feature points in the image plane. This motivates our novel method of tracking multiple targets by cluster analysis of feature points and Multiple particle filters. First, feature points are detected by a Harris corner detector and tracked by a Lucas-Kanade tracker. Clusters of moving targets are then initialized by grouping spatially co-located points with similar motion using the EM algorithm. Due to the non-Gaussian distribution of the points in a cluster and the multi-modality resulting from multiple targets, multiple particle filters are applied to track all the clusters simultaneously: one particle filter is started for one cluster. The proposed method is well Suited for the typical video surveillance configuration where the cameras are still and targets of interest appear relatively small in the image. We demonstrate the effectiveness of our method on different PETS datasets. [less ▲]

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See detailBiomedical image classification with random subwindows and decision trees
Marée, Raphaël ULg; Geurts, Pierre ULg; Piater, Justus ULg et al

in Computer Vision for Biomedical Image Applications (2005)

In this paper, we address a problem of biomedical image classification that involves the automatic classification of x-ray images in 57 predefined classes with large intra-class variability. To achieve ... [more ▼]

In this paper, we address a problem of biomedical image classification that involves the automatic classification of x-ray images in 57 predefined classes with large intra-class variability. To achieve that goal, we apply and slightly adapt a recent generic method for image classification based on ensemble of decision trees and random subwindows. We obtain classification results close to the state of the art on a publicly available database of 10000 x-ray images. We also provide some clues to interpret the classification of each image in terms of subwindow relevance. [less ▲]

Detailed reference viewed: 95 (27 ULg)
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See detailStatistical Learning of Visual Feature Hierarchies
Scalzo, Fabien; Piater, Justus ULg

in Proc. of the IEEE Workshop on Learning in Computer Vision and Pattern Recognition (2005)

Detailed reference viewed: 4 (0 ULg)
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See detailApprentissage non-supervisé de hiérarchies de caractéristiques visuelles
Scalzo, Fabien; Piater, Justus ULg

in Actes du Congrès ORASIS (2005)

Detailed reference viewed: 5 (0 ULg)
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See detailUnsupervised Learning of Visual Feature Hierarchies
Scalzo, Fabien; Piater, Justus ULg

in Proceedings of the International Conference on Machine Learning and Data Mining (MLDM) (2005)

Detailed reference viewed: 7 (0 ULg)
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See detailTracking by cluster analysis of feature points and multiple particle filters
Du, Wei ULg; Piater, Justus ULg

in 3rd International Conference on Advances in Pattern Recognition (2005)

Detailed reference viewed: 9 (0 ULg)
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See detailObject Tracking Using Color Interest Points
Gabriel, Pierre; Hayet, Jean-Bernard; Piater, Justus ULg et al

in International Conference on Advanced Video and Signal based Surveillance (2005)

Detailed reference viewed: 32 (1 ULg)
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See detailRobust Non-Rigid Object Tracking Using Point Distribution Models
Mathes, Tom; Piater, Justus ULg

in British Machine Vision Conference (2005)

Detailed reference viewed: 11 (0 ULg)
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See detailUtilisation des Points d'Intérêts Couleurs pour le Suivi d'Objets
Gabriel, Pierre; Hayet, Jean-Bernard; Piater, Justus ULg et al

in Actes du Congrès ORASIS (2005)

Detailed reference viewed: 38 (1 ULg)
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See detailObject tracking using a combined appearance and geometric model
Gabriel, Pierre F.; Piater, Justus ULg; Verly, Jacques ULg

Conference (2004)

Detailed reference viewed: 2 (0 ULg)
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See detailInteractive Selection of Visual Features through Reinforcement Learning
Jodogne, Sébastien ULg; Piater, Justus ULg

in 24th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence (2004)

Detailed reference viewed: 10 (2 ULg)
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See detailRobust Incremental Rectification of Sports Video Sequences
Hayet, Jean-Bernard; Piater, Justus ULg; Verly, Jacques ULg

in Proceedings of the British Machine Vision Conference (2004)

Detailed reference viewed: 15 (0 ULg)
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See detailIncremental Rectification of Sports Fields in Video Streams With Application to Soccer
Hayet, Jean-Bernard; Piater, Justus ULg; Verly, Jacques ULg

in Advanced Concepts for Intelligent Vision Systems (2004)

Detailed reference viewed: 26 (0 ULg)