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CVPR
2007
IEEE
14 years 7 months ago
Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration
We present a parameter free approach that utilizes multiple cues for image segmentation. Beginning with an image, we execute a sequence of bottom-up aggregation steps in which pix...
Sharon Alpert, Meirav Galun, Ronen Basri, Achi Bra...
PAMI
2010
190views more  PAMI 2010»
13 years 3 months ago
OBJCUT: Efficient Segmentation Using Top-Down and Bottom-Up Cues
—We present a probabilistic method for segmenting instances of a particular object category within an image. Our approach overcomes the deficiencies of previous segmentation tech...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
VLSM
2005
Springer
13 years 10 months ago
Advances in Variational Image Segmentation Using AM-FM Models: Regularized Demodulation and Probabilistic Cue Integration
Current state-of-the-art methods in variational image segmentation using level set methods are able to robustly segment complex textured images in an unsupervised manner. In recent...
Georgios Evangelopoulos, Iasonas Kokkinos, Petros ...
ECCV
2002
Springer
14 years 7 months ago
Probabilistic and Voting Approaches to Cue Integration for Figure-Ground Segmentation
This paper describes techniques for fusing the output of multiple cues to robustly and accurately segment foreground objects from the background in image sequences. Two different m...
Eric Hayman, Jan-Olof Eklundh
CVPR
2012
IEEE
11 years 7 months ago
Segmentation using superpixels: A bipartite graph partitioning approach
Grouping cues can affect the performance of segmentation greatly. In this paper, we show that superpixels (image segments) can provide powerful grouping cues to guide segmentation...
Zhenguo Li, Xiao-Ming Wu, Shih-Fu Chang