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» Graph Cuts and Efficient N-D Image Segmentation
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ECCV
2008
Springer
14 years 9 months ago
Learning Visual Shape Lexicon for Document Image Content Recognition
Developing effective content recognition methods for diverse imagery continues to challenge computer vision researchers. We present a new approach for document image content catego...
Guangyu Zhu, Xiaodong Yu, Yi Li, David S. Doermann
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...
ICCV
2009
IEEE
13 years 5 months ago
Estimating human shape and pose from a single image
We describe a solution to the challenging problem of estimating human body shape from a single photograph or painting. Our approach computes shape and pose parameters of a 3D huma...
Peng Guan, Alexander Weiss, Alexandru O. Balan, Mi...
ICMCS
2006
IEEE
143views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Object Recognition and Recovery by Skeleton Graph Matching
This paper presents a robust and efficient skeleton-based graph matching method for object recognition and recovery applications. The novel feature is to unify both object recogni...
Lei He, Chia Y. Han, William G. Wee
ICDAR
2009
IEEE
13 years 5 months ago
Symbol Detection Using Region Adjacency Graphs and Integer Linear Programming
In this paper, we tackle the problem of localizing graphical symbols on complex technical document images by using an original approach to solve the subgraph isomorphism problem. ...
Pierre Le Bodic, Hervé Locteau, Séba...