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CVPR
2008
IEEE
15 years 11 months ago
Auto-context and its application to high-level vision tasks
The notion of using context information for solving highlevel vision problems has been increasingly realized in the field. However, how to learn an effective and efficient context...
Zhuowen Tu
IJCV
2006
161views more  IJCV 2006»
14 years 9 months ago
Discriminative Random Fields
In this research we address the problem of classification and labeling of regions given a single static natural image. Natural images exhibit strong spatial dependencies, and mode...
Sanjiv Kumar, Martial Hebert
IBPRIA
2003
Springer
15 years 2 months ago
Segmentation of Curvilinear Objects Using a~Watershed-Based Curve Adjacency Graph
Abstract. This paper presents a general framework to segment curvilinear objects in 2D images. A pre-processing step relies on mathematical morphology to obtain a connected line wh...
Thierry Géraud
CVPR
2007
IEEE
15 years 11 months ago
Tracking as Repeated Figure/Ground Segmentation
Tracking over a long period of time is challenging as the appearance, shape and scale of the object in question may vary. We propose a paradigm of tracking by repeatedly segmentin...
Xiaofeng Ren, Jitendra Malik
CVPR
2009
IEEE
16 years 4 months ago
Efficient Scale Space Auto-Context for Image Segmentation and Labeling
The Conditional Random Fields (CRF) model, using patch-based classification bound with context information, has recently been widely adopted for image segmentation/ labeling. In...
Jiayan Jiang (UCLA), Zhuowen Tu (UCLA)