Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour and Texture Analysis for Image Segmentation
International Journal of Computer Vision
Texture Segmentation by Multiscale Aggregation of Filter Responses and Shape Elements
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
Machine Learning
Supervised clustering with support vector machines
ICML '05 Proceedings of the 22nd international conference on Machine learning
Comparing clusterings: an axiomatic view
ICML '05 Proceedings of the 22nd international conference on Machine learning
Toward Objective Evaluation of Image Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Weighted Graph Cuts without Eigenvectors A Multilevel Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Solution stability in linear programming relaxations: graph partitioning and unsupervised learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Contour Detection and Hierarchical Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration
IEEE Transactions on Pattern Analysis and Machine Intelligence
CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Semantic segmentation using regions and parts
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Ensemble Segmentation Using Efficient Integer Linear Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Globally optimal closed-surface segmentation for connectomics
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Fast planar correlation clustering for image segmentation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
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We present a probabilistic model for image segmentation and an efficient approach to find the best segmentation. The image is first grouped into superpixels and a local information is extracted for each pair of spatially adjacent superpixels. The global optimization problem is then cast as correlation clustering which is known to be NP hard. This study demonstrates that in many cases, finding the exact global solution is still feasible by exploiting the characteristics of the image segmentation problem that make it possible to break the problem into subproblems. Each sub-problem corresponds to an automatically detected image part. We demonstrate a reduced computational complexity with comparable results to state-of-the-art on the BSDS-500 and the Weizmann Two-Objects datasets.