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NIPS
2004
13 years 9 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
CVPR
2007
IEEE
14 years 9 months ago
Segmenting Motions of Different Types by Unsupervised Manifold Clustering
We propose a novel algorithm for segmenting multiple motions of different types from point correspondences in multiple affine or perspective views. Since point trajectories associ...
Alvina Goh, René Vidal
ECCV
2006
Springer
13 years 11 months ago
Learning Semantic Scene Models by Trajectory Analysis
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...
Xiaogang Wang, Kinh Tieu, Eric Grimson
DSRT
2005
IEEE
13 years 9 months ago
3D Mesh Compression Using an Efficient Neighborhood-based Segmentation
Due to the popularity of polygonal models in the Virtual Reality applications, 3D mesh compression and segmentation are two active areas of 3D object modeling. Most existing 3D co...
Lijun Chen 0003, Nicolas D. Georganas
CORR
2007
Springer
170views Education» more  CORR 2007»
13 years 7 months ago
The structure of verbal sequences analyzed with unsupervised learning techniques
Data mining allows the exploration of sequences of phenomena, whereas one usually tends to focus on isolated phenomena or on the relation between two phenomena. It offers invaluab...
Catherine Recanati, Nicoleta Rogovschi, Youn&egrav...