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Displaying 1-7 out of 7 total
Learning Hierarchical Features for Scene Labeling
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Clement Farabet,Camille Couprie,Laurent Najman,Yann LeCun
Issue Date:August 2013
pp. 1915-1929
Scene labeling consists of labeling each pixel in an image with the category of the object it belongs to. We propose a method that uses a multiscale convolutional network trained from raw pixels to extract dense feature vectors that encode regions of multi...
 
Hierarchical Video Segmentation Using an Observation Scale
Found in: 2013 XXVI SIBGRAPI - Conference on Graphics, Patterns and Images (SIBGRAPI)
By Kleber Jacques de Souza,Arnaldo de Albuquerque Araujo,Zenilton Kleber G. do Patrocinio,Jean Cousty,Laurent Najman,Yukiko Kenmochi,Silvio Jamil F. Guimaraes
Issue Date:August 2013
pp. 320-327
Hierarchical video segmentation provides region-oriented scale-space, i.e., a set of video segmentations at different detail levels in which the segmentations at finer levels are nested with respect to those at coarser levels. Hierarchical methods have the...
 
Power Watershed: A Unifying Graph-Based Optimization Framework
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Camille Couprie, Leo Grady, Laurent Najman, Hugues Talbot
Issue Date:July 2011
pp. 1384-1399
In this work, we extend a common framework for graph-based image segmentation that includes the graph cuts, random walker, and shortest path optimization algorithms. Viewing an image as a weighted graph, these algorithms can be expressed by means of a comm...
 
Watershed Cuts: Thinnings, Shortest Path Forests, and Topological Watersheds
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Jean Cousty, Gilles Bertrand, Laurent Najman, Michel Couprie
Issue Date:May 2010
pp. 925-939
We recently introduced watershed cuts, a notion of watershed in edge-weighted graphs. In this paper, our main contribution is a thinning paradigm from which we derive three algorithmic watershed cut strategies: The first one is well suited to parallel impl...
 
Watershed Cuts: Minimum Spanning Forests and the Drop of Water Principle
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Jean Cousty, Gilles Bertrand, Laurent Najman, Michel Couprie
Issue Date:August 2009
pp. 1362-1374
We study the watersheds in edge-weighted graphs. We define the watershed cuts following the intuitive idea of drops of water flowing on a topographic surface. We first establish the consistency of these watersheds: They can be equivalently defined by their
 
Indexing Technical Drawings Using Title Block Structure Recognition
Found in: Document Analysis and Recognition, International Conference on
By Laurent Najman,Olivier Gibot,Stéphane Berche
Issue Date:September 2001
pp. 0587
Abstract: This paper presents an application that helps to index archives of technical drawings. Indexing consists in extracting information from the title block in order to ensure document retrieval in a database. The indexing information is usually the d...
 
Geodesic Saliency of Watershed Contours and Hierarchical Segmentation
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Laurent Najman, Michel Schmitt
Issue Date:December 1996
pp. 1163-1173
<p><b>Abstract</b>—The watershed is one of the latest segmentation tools developed in mathematical morphology. In order to prevent its oversegmentation, the notion of dynamics of a minimum, based on geodesic reconstruction, has been propo...
 
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