Machine Learning
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Interactive Graph Cut Based Segmentation with Shape Priors
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Convergent Tree-Reweighted Message Passing for Energy Minimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian, Exemplar-Based Approach to Hierarchical Shape Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
OBJCUT: Efficient Segmentation Using Top-Down and Bottom-Up Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour Detection and Hierarchical Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A compositional exemplar-based model for hair segmentation
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Recursive Segmentation and Recognition Templates for Image Parsing
IEEE Transactions on Pattern Analysis and Machine Intelligence
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In this paper, we propose a novel and effective structural patches tiling procedure which is able to generate high quality probabilistic masks to guide semantic segmentation. In this structural patches tiling procedure, we first apply a local patch structure classifier trained by random forest to the input image in a sliding window manner, and then construct an MRF iteratively optimized to assemble a high quality probabilistic mask from responses collected from the previous stage. Our main contributions are twofold: A patch-based classification procedure which is fast and capable of capturing rich local structures compared with pixel-based ones; a flexible Markovian sliding window merging algorithm which integrates context information into traditional sliding window method. Without loss of generality, we use head-shoulder segmentation to illustrate this procedure's power. Experiments on daily photos and comparisons with previous work demonstrate that we are able to achieve state-of-the-art head-shoulder segmentation results thanks to this structural patches tiling procedure.