Tuesday November 4
| Keynote | 9:00-10:00
Chair: Michael Wilkinson | |
|---|---|---|
| K1 | Georgios Ouzounis | Reinventing the Differential Attribute Profiles |
| Lecture Session 1: Learning-Based Morphology 1 | 10:00-10:50
Chair: Marcos Eduardo Valle | |
| L1.1 | Antoine Bottenmuller, Guillaume Tochon, Romain Hermary, Élodie Puybareau and Gustavo Jesús Angulo | Improving Morphological Networks for Learning Image-to-Image Transforms |
| L1.2 | Mihaela Dimitrova, Samy Blusseau and Santiago Velasco-Forero | Learning Morphological Representations of Image Transformations: Influence of Initialization and Layer Differentiability |
| Coffee Break | 10:50-11:20 | |
| Lecture Session 2: Discrete Geometry -- Models, Transforms, and Visualization | 11:20-13:00
Chair: Andrea Frosini | |
| L2.1 | Lidija Comic, Rita Zrour, Eric Andres and Largeteau-Skapin Gaëlle | An Analytical Definition of Discrete Circles in the Triangular Grid |
| L2.2 | Jacques-Olivier Lachaud and Tristan Roussillon | Convex and concave decomposition of digitized shapes using plane probing and visibility |
| L2.3 | Lysandre Macke, Etienne Baudrier and Etienne Le Quentrec | First Results on Locally Turn-Bounded Surfaces in the 3D Euclidean Space |
| L2.4 | Romain Negro and Jacques-Olivier Lachaud | Fast and exact visibility on digitized shapes and application to saliency-aware normal estimation |
| Lunch Break | 13:00-14:00 | |
| Lecture Session 3: Learning-Based Morphology 2 | 14:00-14:50
Chair: Samy Blusseau | |
| L3.1 | Gustavo Jesús Angulo | A mathematical morphology view of the universal representation of scattering networks |
| L3.2 | Iara Cunha and Marcos Eduardo Valle | Morphological Perceptron with Competitive Layer: Training Using Convex-Concave Procedure |
| IAPR Town Hall | 14:50-15:30 | |
| Coffee Break | 15:30-16:00 | |
| Poster Session | 16:00-18:00 | |
| P1 | Michela Ascolese and Andrea Frosini | Exact polyominoes and non-decomposability |
| P2 | Paul Teeninga and Michael H.F. Wilkinson | Shape Filtering and Max-tree Attribute Computation on a GPU |
| P3 | Arnold Meijster and Mattia Marziali | A linear time algorithm for local minimum and maximum filters |
| P4 | Andrea Frosini and Niccolò Di Marco | Microscopic Image Reconstruction under Convexity Constraints |
| P5 | Shima Shabani, Michael Breuß, Marvin Kahra, Jens Teiser, Gretha Swantje Völke and Nico Wenders | Morphological Granulometric Analysis of Particle Imagery from Microgravity Experiments |
| P6 | François Merciol, Tom Avellaneda, Abdelbadie Belmouhcine and Sébastien Lefèvre | Efficient Content-Based Time Series Retrieval using Pattern Spectra |
| P7 | Diego Marcondes | On the representation of stack operators by mathematical morphology |
| P8 | Jacques-Olivier Lachaud, David Coeurjolly, and Tristan Roussillon | Geometry of Gauss digitized convex shapes |
| P9 | Marcos Eduardo Valle, Santiago Velasco-Forero, Joao Batista Florindo and Gustavo Jesús Angulo | Approximating Condorcet Ordering for Vector-valued Mathematical Morphology |
| P10 | Martin Welk, Andreas Kleefeld, Michael Breuß and Bernhard Burgeth | Morphological PDEs with Rotationally Invariant Space-Fractional Derivatives |
| P11 | Walter Kropatsch | Discrete Spiral and Max-Link, Complementary Tools for Vision |
| P12 | Gabriel Barborosa da Fonseca, Romain Negrel, Benjamin Perret, Jean Cousty, and Silvio Jamil F. Guimarães | Hierarchy-Based Fuzzy Segmentation and Marker Learning |
| P13 | Quentin Lebon, Josselin Lefèvre, Jean Cousty, and Benjamin Perret | Incremental Watershed Cuts: Interactive Segmentation Algorithm with parallel Strategy |
| P14 | Anh Quynh Nguyen, Jean Cousty, Yukiko Kenmochi, and Akinobu Shimizu | Ongoing work on multi-factior component tree loss for topology-aware medical image segmentation |
| P15 | Manel Meftah, Adrien Krähenbühl, and Benoît Naegel | Centerline detection by confidence vote in accumulation map: an extension to grayscale images |
| P16 | Anusha Aswath, Xenia K. Demetriou, Paul D. Teeninga, Bahar Haghigat, Kerstin Bunte, and Michael H.F. Wilkinson | Potato Disease Detection Using Connected Morphological Pattern Spectra and Machine Learning |