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ICIP
2010
IEEE
15 years 4 months ago
Reducing graphs in graph cut segmentation
In few years, graph cuts have become a leading method for solving a wide range of problems in computer vision. However, graph cuts involve the construction of huge graphs which so...
Nicolas Lerme, François Malgouyres, Lucas L...
EMMCVPR
2011
Springer
14 years 6 months ago
High Resolution Segmentation of Neuronal Tissues from Low Depth-Resolution EM Imagery
The challenge of recovering the topology of massive neuronal circuits can potentially be met by high throughput Electron Microscopy (EM) imagery. Segmenting a 3-dimensional stack o...
Daniel Glasner, Tao Hu, Juan Nunez-Iglesias, Lou S...
ECCV
2006
Springer
16 years 8 months ago
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection
This paper introduces the Located Hidden Random Field (LHRF), a conditional model for simultaneous part-based detection and segmentation of objects of a given class. Given a traini...
Ashish Kapoor, John M. Winn
ICPR
2008
IEEE
16 years 1 months ago
Recognition of box-like objects by fusing cues of shape and edges
Boxes are the universal choice for packing, storage, and transportation. In this paper we propose a template-based algorithm for recognition of box-like objects, which is invarian...
Chia-Chih Chen, Jake K. Aggarwal
ICPR
2008
IEEE
16 years 1 months ago
Graph cut based deformable model with statistical shape priors
This paper presents a novel graph cut based segmentation approach with shape priors. The model incorporates statistical shape prior information with the active contour without edg...
Noha Youssry El-Zehiry, Adel Elmaghraby