Join, select, and insert: efficient out-of-core algorithms for hierarchical segmentation trees

Binary Partition Hierarchies (BPH) and minimum spanning trees are fundamental data structures involved in hierarchical analysis such as quasi-flat zones or watershed. However, classical BPH construction algorithms require to have the whole data in memory, which prevent the processing of large images that cannot fit entirely in the main memory of the computer. To cope with this problem, an algebraic framework leading to a high level calculus was introduced allowing an out-of-core computation of BPHs. This calculus relies on three operations: select, join, and insert. In this article, we introduce three efficient algorithms to perform these operations providing pseudo-code and complexity analysis

Join, select, and insert: efficient out-of-core algorithms for hierarchical segmentation trees

International audienceBinary Partition Hierarchies (BPH) and minimum spanning trees are fundamental data structures involved in hierarchical analysis such as quasi-flat zones or watershed. However, classical BPH construction algorithms require to have the whole data in memory, which prevent the processing of large images that cannot fit entirely in the main memory of the computer. To cope with this problem, an algebraic framework leading to a high level calculus was introduced allowing an out-of-core computation of BPHs. This calculus relies on three operations: select, join, and insert. In this article, we introduce three efficient algorithms to perform these operations providing pseudo-code and complexity analysis

Out-of-core Attribute Algorithms for Binary Partition Hierarchies

Binary Partition Hierarchies (BPHs) and Minimum Spanning Trees are key structures in hierarchical image analysis. However, the explosion in the size of image data poses a new challenge, as the memory available in conventional workstations becomes insufficient to execute classical algorithms. To address this problem, specific algorithms have been proposed for out-of-core computation of BPHs, where a BPH is actually represented by a collection of smaller trees, called a distribution, thus reducing the memory footprint of the algorithms. In this article, we address the problem of designing efficient out-of-core algorithms for computing classical attributes in distributions of BPHs, which is a necessary step towards a complete out-of-core hierarchical analysis workflow that includes tasks such as connected filtering and the generation of other representations such as hierarchical watersheds. The proposed algorithms are based on generic operations designed to propagate information through the distribution of trees, enabling the computation of attributes such as area, volume, height, minima and number of minima

Join, select, and insert: efficient out-of-core algorithms for hierarchical segmentation trees

International audienceBinary Partition Hierarchies (BPH) and minimum spanning trees are fundamental data structures involved in hierarchical analysis such as quasi-flat zones or watershed. However, classical BPH construction algorithms require to have the whole data in memory, which prevent the processing of large images that cannot fit entirely in the main memory of the computer. To cope with this problem, an algebraic framework leading to a high level calculus was introduced allowing an out-of-core computation of BPHs. This calculus relies on three operations: select, join, and insert. In this article, we introduce three efficient algorithms to perform these operations providing pseudo-code and complexity analysis

Interactive Segmentation With Incremental Watershed Cuts

International audienceIn this article, we propose an incremental method for computing seeded watershed cuts for interactive image segmentation. We propose an algorithm based on the hierarchical image representation called the binary partition tree to compute a seeded watershed cut. We show that this algorithm fits perfectly in an interactive segmentation process by handling user interactions, seed addition or removal, in time linear with respect to the number of affected pixels. Run time comparisons with several state-of-the-art interactive and noninteractive watershed methods show that the proposed method can handle user interactions much faster than previous methods, thus improving the user experience on large images

Join, select, and insert: efficient out-of-core algorithms for hierarchical segmentation trees

International audienceBinary Partition Hierarchies (BPH) and minimum spanning trees are fundamental data structures involved in hierarchical analysis such as quasi-flat zones or watershed. However, classical BPH construction algorithms require to have the whole data in memory, which prevent the processing of large images that cannot fit entirely in the main memory of the computer. To cope with this problem, an algebraic framework leading to a high level calculus was introduced allowing an out-of-core computation of BPHs. This calculus relies on three operations: select, join, and insert. In this article, we introduce three efficient algorithms to perform these operations providing pseudo-code and complexity analysis

L'Union européenne à l'épreuve de ses territoires

numéro dirigé par Bernard Elissalde et Frédéric Santamaria numéro suivi par Emmanuelle Boulinea

Les violences sexistes après #MeToo

À partir d’octobre 2017, #MeToo devient un phénomène mondial, en diffusant internationalement le slogan que Tarana Burke, militante new-yorkaise contre les violences sexuelles, avait lancé dix ans plus tôt. Une multitude de victimes témoignent sur divers supports numériques et médiatiques, reformulant et intensifiant des luttes féministes en cours contre les violences sexistes. À l’initiative d’une nouvelle génération de chercheuses et chercheurs francophones sur les violences de genre, ce premier ouvrage académique en France sur #MeToo cherche à comprendre l’événement. Il propose une approche empirique de ce mouvement mondial. Il décrypte d’abord l’événement #MeToo dans sa matérialité, ses contextes de réception et d’appropriation et s’efforce de montrer comment l’usage des réseaux socionumériques permet d’articuler de nouvelles formes de militantisme ou de renforcer des pratiques militantes existantes en ligne et hors ligne. Il inscrit ensuite #MeToo dans une histoire des luttes féministes de plus long terme et s’efforce de questionner son unité à travers l’étude de ses résonances contrastées dans différents milieux professionnels