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42 results on '"Van Hamme, David"'

1. Segmentation of Range-Azimuth Maps of FMCW Radars with a Deep Convolutional Neural Network

Author

Meiresone, Pieter, Van Hamme, David, Philips, Wilfried, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Blanc-Talon, Jaques, editor, Delmas, Patrice, editor, Philips, Wilfried, editor, and Scheunders, Paul, editor

Published
2023
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3. Figure 3 from: Paoletti S, Rumes B, Pierantonio N, Panigada S, Jan R, Folegot T, Schilling A, Riviere N, Carrier V, Dumoulin A, Van Hamme D, Marquis-Laisné G, Bruliard F-A, Petitpierre F, Demoor D (2023) SEADETECT: developing an automated detection system to reduce whale-vessel collision risk. Research Ideas and Outcomes 9: e113968. https://doi.org/10.3897/rio.9.e113968

Author

Paoletti, Silvia, primary, Rumes, Bob, additional, Pierantonio, Nino, additional, Panigada, Simone, additional, Jan, Romain, additional, Folegot, Thomas, additional, Schilling, Anita, additional, Riviere, Nicolas, additional, Carrier, Vincent, additional, Dumoulin, Antoine, additional, Van Hamme, David, additional, Marquis-Laisné, Gildas, additional, Bruliard, François-Antoine, additional, Petitpierre, Félix, additional, and Demoor, Damien, additional

Published
2023
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4. SEADETECT: developing an automated detection system to reduce whale-vessel collision risk

Author

Paoletti, Silvia, primary, Rumes, Bob, additional, Pierantonio, Nino, additional, Panigada, Simone, additional, Jan, Romain, additional, Folegot, Thomas, additional, Schilling, Anita, additional, Riviere, Nicolas, additional, Carrier, Vincent, additional, Dumoulin, Antoine, additional, Van Hamme, David, additional, Marquis-Laisné, Gildas, additional, Bruliard, François-Antoine, additional, Petitpierre, Félix, additional, and Demoor, Damien, additional

Published
2023
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5. Figure 1 from: Paoletti S, Rumes B, Pierantonio N, Panigada S, Jan R, Folegot T, Schilling A, Riviere N, Carrier V, Dumoulin A, Van Hamme D, Marquis-Laisné G, Bruliard F-A, Petitpierre F, Demoor D (2023) SEADETECT: developing an automated detection system to reduce whale-vessel collision risk. Research Ideas and Outcomes 9: e113968. https://doi.org/10.3897/rio.9.e113968

Author

Paoletti, Silvia, primary, Rumes, Bob, additional, Pierantonio, Nino, additional, Panigada, Simone, additional, Jan, Romain, additional, Folegot, Thomas, additional, Schilling, Anita, additional, Riviere, Nicolas, additional, Carrier, Vincent, additional, Dumoulin, Antoine, additional, Van Hamme, David, additional, Marquis-Laisné, Gildas, additional, Bruliard, François-Antoine, additional, Petitpierre, Félix, additional, and Demoor, Damien, additional

Published
2023
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6. Figure 2 from: Paoletti S, Rumes B, Pierantonio N, Panigada S, Jan R, Folegot T, Schilling A, Riviere N, Carrier V, Dumoulin A, Van Hamme D, Marquis-Laisné G, Bruliard F-A, Petitpierre F, Demoor D (2023) SEADETECT: developing an automated detection system to reduce whale-vessel collision risk. Research Ideas and Outcomes 9: e113968. https://doi.org/10.3897/rio.9.e113968

Author

Paoletti, Silvia, primary, Rumes, Bob, additional, Pierantonio, Nino, additional, Panigada, Simone, additional, Jan, Romain, additional, Folegot, Thomas, additional, Schilling, Anita, additional, Riviere, Nicolas, additional, Carrier, Vincent, additional, Dumoulin, Antoine, additional, Van Hamme, David, additional, Marquis-Laisné, Gildas, additional, Bruliard, François-Antoine, additional, Petitpierre, Félix, additional, and Demoor, Damien, additional

Published
2023
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11. Cell-Based Approach for 3D Reconstruction from Incomplete Silhouettes

Author

Slembrouck, Maarten, Veelaert, Peter, Van Hamme, David, Van Cauwelaert, Dimitri, Philips, Wilfried, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Blanc-Talon, Jacques, editor, Penne, Rudi, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2017
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12. C-EFIC: Color and Edge Based Foreground Background Segmentation with Interior Classification

Author

Allebosch, Gianni, Van Hamme, David, Deboeverie, Francis, Veelaert, Peter, Philips, Wilfried, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Liu, Ting, Series editor, Kotenko, Igor, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Braz, José, editor, Pettré, Julien, editor, Richard, Paul, editor, Kerren, Andreas, editor, Linsen, Lars, editor, Battiato, Sebastiano, editor, and Imai, Francisco, editor

Published
2016
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13. A Visual SLAM System on Mobile Robot Supporting Localization Services to Visually Impaired People

Author

Nguyen, Quoc-Hung, Vu, Hai, Tran, Thanh-Hai, Van Hamme, David, Veelaert, Peter, Philips, Wilfried, Nguyen, Quang-Hoan, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Agapito, Lourdes, editor, Bronstein, Michael M., editor, and Rother, Carsten, editor

Published
2015
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16. Bringing pedestrian detection for autos to the next level

Author

Aelterman, Jan and Van Hamme, David

Subjects
Remote sensing, Traffic safety, Sensors, Radar systems, Electronics and electrical industries
Abstract

Byline: Jan Aelterman and David Van Hamme Studies from the National Highway Traffic Safety Administration (NHTSA) show that human error (e.g., speeding, fatigue, and drunk or distracted driving) causes 94 [...]

Published
2021

18. Robust Visual Odometry Using Uncertainty Models

Author

Van Hamme, David, Veelaert, Peter, Philips, Wilfried, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Blanc-Talon, Jacques, editor, Kleihorst, Richard, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2011
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19. Combining Geometric Edge Detectors for Feature Detection

Author

Heyvaert, Michaël, Van Hamme, David, Coppens, Jonas, Veelaert, Peter, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Blanc-Talon, Jacques, editor, Bone, Don, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2010
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20. Fire Detection in Color Images Using Markov Random Fields

Author

Van Hamme, David, Veelaert, Peter, Philips, Wilfried, Teelen, Kristof, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Blanc-Talon, Jacques, editor, Bone, Don, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2010
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21. Foliage Recognition Based on Local Edge Information

Author

Van Hamme, David, Veelaert, Peter, Philips, Wilfried, Teelen, Kristof, Stevens, Niels, Vermeersch, Bart, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Blanc-Talon, Jacques, editor, Bourennane, Salah, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2008
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32. Self-learning voxel-based multi-camera occlusion maps for 3D reconstruction

Author

Slembrouck, Maarten, Van Cauwelaert, Dimitri, Van Hamme, David, Van Haerenborgh, Dirk, Van Hese, Peter, Veelaert, Peter, Philips, Wilfried, Battiato, Sebastiano, and Braz, José

Subjects
Multi-camera, Technology and Engineering, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Visual hull, Occlusion Detection, Self-learning, GeneralLiterature_MISCELLANEOUS, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

The quality of a shape-from-silhouettes 3D reconstruction technique strongly depends on the completeness of the silhouettes from each of the cameras. Static occlusion, due to e.g. furniture, makes reconstruction difficult, as we assume no prior knowledge concerning shape and size of occluding objects in the scene. In this paper we present a self-learning algorithm that is able to build an occlusion map for each camera from a voxel perspective. This information is then used to determine which cameras need to be evaluated when reconstructing the 3D model at every voxel in the scene. We show promising results in a multi-camera setup with seven cameras where the object is significantly better reconstructed compared to the state of the art methods, despite the occluding object in the center of the room.

Published
2014

34. Efficient detection of crossing pedestrians from a moving vehicle with an array of cameras.

Author

Allebosch, Gianni, Van Hamme, David, Veelaert, Peter, and Philips, Wilfried

Subjects
*PEDESTRIAN crosswalks, *IMAGE processing, *PEDESTRIANS, *DETECTORS, *MOTOR vehicle driving, *CAMERAS, *VEHICLES
Abstract

We describe a method for detecting crossing pedestrians and, in general, any object that is moving perpendicular to the driving direction of the vehicle. This is achieved by combining video snapshots from multiple cameras that are placed in a linear configuration and from multiple time instances. We demonstrate that the proposed array configuration imposes tight constraints on the expected disparity of static objects in a certain image region for a given camera pair. These regions are distinct for different camera pairs. In that manner, static regions can generally be distinguished from moving targets throughout the entire field of view when analyzing enough pairs, requiring only straightforward image processing techniques. On a self-captured dataset with crossing pedestrians, our proposed method reaches an F1 detection score of 83.66% and a mean average precision (MAP) of 84.79% on an overlap test when used stand-alone, being processed at 59 frames per second without GPU acceleration. When combining it with the Yolo V4 object detector in cooperative fusion, the proposed method boosts the maximal F1 scores of this detector on this same dataset from 87.86% to 92.68% and the MAP from 90.85% to 94.30%. Furthermore, combining it with the lower power Yolo-Tiny V4 detector in the same way yields F1 and MAP increases from 68.57% to 81.16% and 72.32% to 85.25%, respectively. [ABSTRACT FROM AUTHOR]

Published
2023
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39. Cycling around bends

Author

Vansteenkiste, Pieter, primary, Van Hamme, David, additional, Cardon, Greet, additional, and Lenoir, Matthieu, additional

Published
2013
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42. Time complexity of traditional vision algorithms on a block-based image processor (BLIP).

Author

Slembrouck, Maarten, Heyvaert, Michael, Van Cauwelaert, Dimitri, Van Hamme, David, Veelaert, Peter, and Philips, Wilfried

Abstract

Generally, image processing algorithms are suitable for parallel execution. However, this has not yet been exploited in a feasible design. Instead of the common practice, where the pixels on the sensor and the processor arrays are mapped onto each other, we propose the idea to split the image into multiple blocks of pixels (of the same size) and map each of these blocks onto one processing element. This decreases the hardware consumption and the communication overhead between the processing elements. This paper describes the architecture of the processor (the block-based image processor, BLIP) and the feasibility of low-, mid- and high-level image processing algorithms on the proposed architecture. [ABSTRACT FROM PUBLISHER]

Published
2012

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