Now showing items 1-5 of 5
Augmented Lagrangian method for an Euler's elastica based segmentation model that promotes convex contours
In this paper, we propose an image segmentation model where an L1 variant of the Euler's elastica energy is used as boundary regularization. An interesting feature of this model lies in its preference for convex segmentation ...
Simplified energy landscape for modularity using total variation
Networks capture pairwise interactions between entities and are frequently used in applications such as social networks, food networks, and protein interaction networks, to name a few. Communities, cohesive groups of nodes, ...
Convex Variational Methods on Graphs for Multiclass Segmentation of High-Dimensional Data and Point Clouds
Graph-based variational methods have recently shown to be highly competitive for various classification problems of high-dimensional data, but are inherently difficult to handle from an optimization perspective. This ...
Automatic scene understanding and object identification in point clouds
A ladar can acquire a dense set of 3D coordinates of a scene, a so-called point cloud, in sub-second time from ranges of several kilometers. This paper presents algorithms for segmenting a point cloud into meaningful classes ...
Automatic object recognition within point clouds in clustered or scattered scenes
We consider the problem of automatically locating, classifying and identifying an object within a point cloud that has been acquired by scanning a scene with a ladar. The recent work [E. Bae, Automatic scene understanding ...