Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
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
Computer Vision
Learning a Classification Model for Segmentation
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
ACM SIGGRAPH 2004 Papers
"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
A Multilevel Banded Graph Cuts Method for Fast Image Segmentation
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Boundary Extraction in Natural Images Using Ultrametric Contour Maps
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Interactive image segmentation by maximal similarity based region merging
Pattern Recognition
A comparative study of energy minimization methods for markov random fields
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Error-tolerant interactive image segmentation using dynamic and iterated graph-cuts
Proceedings of the 2nd ACM international workshop on Interactive multimedia on mobile and portable devices
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We propose a novel and fast interactive image segmentation algorithm for use on mobile phones. Instead of using global optimization, our algorithm begins with an initial over-segmentation using the mean shift algorithm and follows this by discriminative clustering and local neighborhood classification. This procedure obtains better quality results than previous methods that use graph cuts on oversegmented regions or region merging based on maximal similarity, yet its running time is smaller by an order of magnitude. We compare and analyze the strengths and limitations of the three approaches and have implemented our algorithm as part of an interactive object cut out application running on a mobile phone.