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» Supervised Image Segmentation Using Markov Random Fields
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DAGM
2010
Springer
15 years 27 days ago
Probabilistic Multi-class Scene Flow Segmentation for Traffic Scenes
A multi-class traffic scene segmentation approach based on scene flow data is presented. Opposed to many other approaches using color or texture features, our approach is purely ba...
Alexander Barth, Jan Siegemund, Annemarie Mei&szli...
CVPR
2009
IEEE
16 years 7 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
CVPR
2008
IEEE
16 years 1 months ago
Principled fusion of high-level model and low-level cues for motion segmentation
High-level generative models provide elegant descriptions of videos and are commonly used as the inference framework in many unsupervised motion segmentation schemes. However, app...
Arasanathan Thayananthan, Masahiro Iwasaki, Robert...
CVPR
2009
IEEE
16 years 7 months ago
Nonparametric Scene Parsing: Label Transfer via Dense Scene Alignment
In this paper we propose a novel nonparametric approach for object recognition and scene parsing using dense scene alignment. Given an input image, we retrieve its best matches ...
Antonio B. Torralba, Ce Liu, Jenny Yuen
AIA
2007
15 years 1 months ago
Classification of biomedical high-resolution micro-CT images for direct volume rendering
This paper introduces a machine learning approach into the process of direct volume rendering of biomedical highresolution 3D images. More concretely, it proposes a learning pipel...
Maite López-Sánchez, Jesús Ce...