Dr. Wyke Pereboom-Huizinga Profile

Dr. Wyke Pereboom-Huizinga

at TNO

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Author

Publications (11)

Proceedings Article | 13 November 2024 Presentation + Paper

On the use of appearance features for multiple object tracking in a maritime scenario

Luca Ballan, Richard J. den Hollander, Jan Baan, Friso Heslinga, Wyke Huizinga

Proceedings Volume 13207, 132070D (2024) https://doi.org/10.1117/12.3031500

KEYWORDS: Feature extraction, Data modeling, Object detection, Situational awareness sensors

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Proceedings Article | 7 June 2024 Presentation + Paper

Improving object detector training on synthetic data by starting with a strong baseline methodology

Frank Ruis, Alma Liezenga, Friso Heslinga, Luca Ballan, Thijs Eker, Richard J. den Hollander, Martin van Leeuwen, Judith Dijk, Wyke Huizinga

Proceedings Volume 13035, 1303511 (2024) https://doi.org/10.1117/12.3013441

KEYWORDS: Data modeling, Object detection, Transformers, Education and training, Performance modeling, 3D modeling, Sensors, Visual process modeling, Linear filtering, Computer vision technology

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Proceedings Article | 7 June 2024 Presentation + Paper

EO and radar fusion for fine-grained target classification with a strong few-shot learning baseline

Luca Ballan, Jorge G. Melo, Sebastiaan van den Broek, Jan Baan, Friso Heslinga, Wyke Huizinga, Judith Dijk, Arta Dilo

Proceedings Volume 13057, 130570K (2024) https://doi.org/10.1117/12.3013756

KEYWORDS: Data modeling, Machine learning, Image classification, Visualization, Radar, Sensors, Deep learning

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Combining data from multiple sensors to improve the overall robustness and reliability of a classification system has become crucial in many applications, from military surveillance and decision support, to autonomous driving, robotics, and medical imaging. This so-called sensor fusion is especially interesting for fine-grained target classification, in which very specific sub-categories (e.g. ship types) need to be distinguished, a task that can be challenging with data from a single modality. Typical modalities are electro-optical (EO) image sensors, that can provide rich visual details of an object of interest, and radar, that can yield additional spatial information. Defined by the approach used to combine data from these sensors, several fusion techniques exist. For example, late fusion can merge class probabilities outputted by separate processing pipelines dedicated to each of the individual sensor data. In particular, deep learning (DL) has been widely leveraged for EO image analysis, but typically requires a lot of data to adapt to the nuances of a fine-grained classification task. Recent advances in DL on foundation models have shown a high potential when dealing with in-domain data scarcity, especially in combination with few-shot learning. This paper presents a framework to effectively combine EO and radar sensor data, and shows how this method outperforms stand-alone single sensor methods for fine-grained target classification. We adopt a strong few-shot image classification baseline based on foundation models, which robustly handles the lack of in-domain data and exploits rich visual features. In addition, we investigate a weighted and a Bayesian fusion approach to combine target class probabilities outputted by the image classification model and radar kinematic features. Experiments with data acquired in a measurement campaign at the port of Rotterdam show that our fusion method improves on the classification performance of individual modalities.

Proceedings Article | 17 October 2023 Presentation + Paper

Aerial image segmentation with minimal annotation effort using clustering of pretrained embeddings

Sabina van Rooij, Maarten Kruithof, Wyke Huizinga, Gertjan Burghouts, Klamer Schutte

Proceedings Volume 12742, 127420M (2023) https://doi.org/10.1117/12.2688450

KEYWORDS: Image segmentation, Education and training, Data modeling, Semantics, Performance modeling, Clutter, Buildings, Remote sensing, Prototyping, Dimension reduction

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Proceedings Article | 17 October 2023 Presentation + Paper

Leveraging temporal context in deep learning methodology for small object detection

Friso Heslinga, Frank Ruis, Luca Ballan, Martin van Leeuwen, Beatrice Masini, Jan Erik van Woerden, Richard J. den Hollander, Martin Berndsen, Jan Baan, Judith Dijk, Wyke Huizinga

Proceedings Volume 12742, 127420H (2023) https://doi.org/10.1117/12.2675589

KEYWORDS: Object detection, Video, Deep learning, Infrared cameras, Image segmentation

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Proceedings Article | 17 October 2023 Presentation + Paper

Ship detection in thermal infrared using paired visible light images and domain adaptation via knowledge distillation

Jorge G. O. Melo, Luca Ballan, Bas S. P. van den Broek, Jan Baan, Judith Dijk, Wyke Huizinga, Arta Dilo

Proceedings Volume 12742, 127420K (2023) https://doi.org/10.1117/12.2680071

KEYWORDS: Object detection, Education and training, Performance modeling, Data modeling, Sensors, Thermography, Visible radiation, Video surveillance, Surveillance, Infrared radiation

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Proceedings Article | 15 September 2021 Presentation + Paper

Automated operator support for vessel threat assessment

Wyke Huizinga, Michel van Lier, Maarten Kruithof, Judith Dijk

Proceedings Volume 11870, 1187006 (2021) https://doi.org/10.1117/12.2600802

KEYWORDS: Weapons, Cameras, Data modeling, Sensors, Performance modeling, Video, Detection and tracking algorithms, Image quality

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Proceedings Article | 20 September 2020 Presentation + Paper

Long-range person and vehicle detection

Bob van den Hoogen, Wouter Uijens, Richard den Hollander, Wyke Huizinga, Judith Dijk, Klamer Schutte

Proceedings Volume 11543, 115430B (2020) https://doi.org/10.1117/12.2582373

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SPIE Journal Paper | 11 July 2019

Evaluation of detection and tracking performance in imaging systems

Wyke Huizinga, Annegreet Van Opbroek, Raimon H. Pruim, Richard J. den Hollander, Sebastiaan van den Broek, Emma Schook, Klamer Schutte, Nanda van der Stap, Judith Dijk

OE, Vol. 58, Issue 07, 073103, (July 2019) https://doi.org/10.1117/12.10.1117/1.OE.58.7.073103

KEYWORDS: Imaging systems, Video, Surveillance, Detection and tracking algorithms, Sensors, Optical engineering, Target detection, Sensor performance, Video surveillance, Automatic tracking

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Proceedings Article | 9 October 2018 Presentation + Paper

Maritime detection framework 2.0: a new approach of maritime target detection in electro-optical sensors

Nanda van der Stap, Annegreet van Opbroek, Wyke Huizinga, Mike Wilmer, Bas van den Broek, Raimon Pruim, Richard den Hollander, Klamer Schutte, Judith Dijk

Proceedings Volume 10795, 1079507 (2018) https://doi.org/10.1117/12.2501424

KEYWORDS: Sensors, Target detection, Mid-IR, Long wavelength infrared, Cameras, Detection and tracking algorithms, Electro optical sensors, Detector development, Image segmentation, Algorithm development

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Proceedings Article | 29 March 2016 Paper

Modeling the brain morphology distribution in the general aging population

W. Huizinga, D. H. Poot, G. Roshchupkin, E. Bron, M. Ikram, M. Vernooij, D. Rueckert, W. Niessen, S. Klein

Proceedings Volume 9788, 97880I (2016) https://doi.org/10.1117/12.2207228

KEYWORDS: Brain, Neuroimaging, Image registration, Visualization, Statistical analysis, Magnetic resonance imaging, Alzheimer's disease, Visual analytics, Radiology, Image analysis

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Showing 5 of 11 publications

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