Results 1 - 10 of 68,996

Efficient graph-based image segmentation.

by Pedro F Felzenszwalb , Daniel P Huttenlocher - International Journal of Computer Vision, , 2004
"... Abstract. This paper addresses the problem of segmenting an image into regions. We define a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image. We then develop an efficient segmentation algorithm based on this predicate, and show ..."
Abstract - Cited by 940 (1 self) - Add to MetaCart
that although this algorithm makes greedy decisions it produces segmentations that satisfy global properties. We apply the algorithm to image segmentation using two different kinds of local neighborhoods in constructing the graph, and illustrate the results with both real and synthetic images. The algorithm

Maximum entropy markov models for information extraction and segmentation

by Andrew McCallum, Dayne Freitag, Fernando Pereira , 2000
"... Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech tagging, text segmentation and information extraction. In these cases, the observations are usually modeled as multinomial ..."
Abstract - Cited by 561 (18 self) - Add to MetaCart
present positive experimental results on the segmentation of FAQ’s.

Conditional random fields: Probabilistic models for segmenting and labeling sequence data

by John Lafferty , 2001
"... We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hidden Markov models and stochastic grammars for such tasks, including the ability to relax strong independence assumptions ..."
Abstract - Cited by 3485 (85 self) - Add to MetaCart
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hidden Markov models and stochastic grammars for such tasks, including the ability to relax strong independence assumptions

Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D Images

by Yuri Y. Boykov , Marie-Pierre Jolly , 2001
"... In this paper we describe a new technique for general purpose interactive segmentation of N-dimensional images. The user marks certain pixels as “object” or “background” to provide hard constraints for segmentation. Additional soft constraints incorporate both boundary and region information. Graph ..."
Abstract - Cited by 1010 (20 self) - Add to MetaCart
” segments may consist of several isolated parts. Some experimental results are presented in the context of photo/video editing and medical image segmentation. We also demonstrate an interesting Gestalt example. A fast implementation of our segmentation method is possible via a new max-flow algorithm in [2].

Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm

by Yongyue Zhang, Michael Brady, Stephen Smith - IEEE TRANSACTIONS ON MEDICAL. IMAGING , 2001
"... The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogram-based model, the FM has an intrinsic limi ..."
Abstract - Cited by 639 (15 self) - Add to MetaCart
The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogram-based model, the FM has an intrinsic

A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model

by Luminita A. Vese, Tony F. Chan - INTERNATIONAL JOURNAL OF COMPUTER VISION , 2002
"... We propose a new multiphase level set framework for image segmentation using the Mumford and Shah model, for piecewise constant and piecewise smooth optimal approximations. The proposed method is also a generalization of an active contour model without edges based 2-phase segmentation, developed by ..."
Abstract - Cited by 498 (22 self) - Add to MetaCart
on The Four-Color Theorem. Finally, we validate the proposed models by numerical results for signal and image denoising and segmentation, implemented using the Osher and Sethian level set method.

Histograms of Oriented Gradients for Human Detection

by Navneet Dalal, Bill Triggs - In CVPR , 2005
"... We study the question of feature sets for robust visual object recognition, adopting linear SVM based human detection as a test case. After reviewing existing edge and gradient based descriptors, we show experimentally that grids of Histograms of Oriented Gradient (HOG) descriptors significantly out ..."
Abstract - Cited by 3735 (9 self) - Add to MetaCart
outperform existing feature sets for human detection. We study the influence of each stage of the computation on performance, concluding that fine-scale gradients, fine orientation binning, relatively coarse spatial binning, and high-quality local contrast normalization in overlapping descriptor blocks

Cluster Ensembles - A Knowledge Reuse Framework for Combining Multiple Partitions

by Alexander Strehl, Joydeep Ghosh, Claire Cardie - Journal of Machine Learning Research , 2002
"... This paper introduces the problem of combining multiple partitionings of a set of objects into a single consolidated clustering without accessing the features or algorithms that determined these partitionings. We first identify several application scenarios for the resultant 'knowledge reuse&ap ..."
Abstract - Cited by 603 (20 self) - Add to MetaCart
' framework that we call cluster ensembles. The cluster ensemble problem is then formalized as a combinatorial optimization problem in terms of shared mutual information. In addition to a direct maximization approach, we propose three effective and efficient techniques for obtaining high-quality combiners

The 2005 pascal visual object classes challenge

by Mark Everingham, Andrew Zisserman, Christopher K. I. Williams, Luc Van Gool, Moray Allan, Christopher M. Bishop, Olivier Chapelle, Navneet Dalal, Thomas Deselaers, Gyuri Dorkó, Stefan Duffner, Jan Eichhorn, Jason D. R. Farquhar, Mario Fritz, Christophe Garcia, Tom Griffiths, Frederic Jurie, Daniel Keysers, Markus Koskela, Jorma Laaksonen, Diane Larlus, Bastian Leibe, Hongying Meng, Hermann Ney, Bernt Schiele, Cordelia Schmid, Edgar Seemann, John Shawe-taylor, Amos Storkey, Or Szedmak, Bill Triggs, Ilkay Ulusoy, Ville Viitaniemi, Jianguo Zhang , 2006
"... Abstract. The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic scenes (i.e. not pre-segmented objects). Four object classes were selected: motorbikes, bicycles, cars and peop ..."
Abstract - Cited by 649 (23 self) - Add to MetaCart
Abstract. The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic scenes (i.e. not pre-segmented objects). Four object classes were selected: motorbikes, bicycles, cars

"GrabCut” -- interactive foreground extraction using iterated graph cuts

by Carsten Rother, Vladimir Kolmogorov, Andrew Blake - ACM TRANS. GRAPH , 2004
"... The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Classical image segmentation tools use either texture (colour) information, e.g. Magic Wand, or edge (contrast) information, e.g. Intelligent Scissors. Recently ..."
Abstract - Cited by 1130 (36 self) - Add to MetaCart
of the iterative algorithm is used to simplify substantially the user interaction needed for a given quality of result. Thirdly, a robust algorithm for “border matting ” has been developed to estimate simultaneously the alpha-matte around an object boundary and the colours of foreground pixels. We show
Results 1 - 10 of 68,996