TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context

Keywords

Artificial intelligenceDiscriminative modelComputer scienceConditional random fieldSegmentationPattern recognition (psychology)Boosting (machine learning)Classifier (UML)Image segmentationComputer visionPixelUnary operationMathematics

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Publication Info

Year: 2007
Type: article
Volume: 81
Issue: 1
Pages: 2-23
Citations: 1040
Access: Closed

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APA Style

                            
                                
                                    Jamie Shotton, 
                                
                                    John Winn, 
                                
                                    Carsten Rother
                                
                                et al.
                            
                            (2007). 
                            TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context. 
                            International Journal of Computer Vision
                            , 81
                            (1)
                            , 2-23.
                            https://doi.org/10.1007/s11263-007-0109-1
                        

Identifiers

DOI: 10.1007/s11263-007-0109-1