Superpixel lattices

Alastair Moore; Simon J. D. Prince; Jonathan Warrell; Umar Mohammed; Graham Jones

doi:10.1109/cvpr.2008.4587471

Abstract

Unsupervised over-segmentation of an image into superpixels is a common preprocessing step for image parsing algorithms. Ideally, every pixel within each superpixel region will belong to the same real-world object. Existing algorithms generate superpixels that forfeit many useful properties of the regular topology of the original pixels: for example, the nth superpixel has no consistent position or relationship with its neighbors. We propose a novel algorithm that produces superpixels that are forced to conform to a grid (a regular superpixel lattice). Despite this added topological constraint, our algorithm is comparable in terms of speed and accuracy to alternative segmentation approaches. To demonstrate this, we use evaluation metrics based on (i) image reconstruction (ii) comparison to human-segmented images and (iii) stability of segmentation over subsequent frames of video sequences.

Keywords

Artificial intelligencePixelComputer sciencePattern recognition (psychology)SegmentationImage segmentationPreprocessorParsingImage (mathematics)Computer vision

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Publication Info

Year: 2008
Type: article
Pages: 1-8
Citations: 372
Access: Closed

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APA Style

                            
                                    Alastair Moore, 
                                
                                    Simon J. D. Prince, 
                                
                                    Jonathan Warrell
                                
                                et al.
                            
                            (2008). 
                            Superpixel lattices. 
                            
                            , 1-8.
                            https://doi.org/10.1109/cvpr.2008.4587471

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DOI: 10.1109/cvpr.2008.4587471