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Adaptive high-precision superpixel segmentation
Multimedia Tools and Applications, 2018Superpixel as a fundamental processing unit can significantly reduce the computational complexity of subsequent computer vision tasks. In this paper, an Adaptive High-Precision (AHP) superpixel segmentation algorithm is proposed. Three major schemes are proposed in this algorithm.
Xinlin Xie +3 more
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4D Light Field Superpixel and Segmentation
IEEE Transactions on Image Processing, 2020Superpixel segmentation of 2D images has been widely used in many computer vision tasks. Previous algorithms model the color, position, or higher spectral information for segmenting a 2D image. However, limited to the Gaussian imaging principle in a traditional camera, where each pixel is formed by summing lots of light rays from different angles ...
Hao Zhu 0005 +3 more
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Image Segmentation by Bilayer Superpixel Grouping
2013 2nd IAPR Asian Conference on Pattern Recognition, 2013The task of image segmentation is to group image pixels into visually meaningful objects. It has long been a challenging problem in computer vision and image processing. In this paper we address the segmentation as a super pixel grouping problem. We propose a novel graph-based segmentation framework which is able to integrate different cues from ...
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4D Light Field Superpixel and Segmentation
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017Superpixel segmentation of 2D image has been widely used in many computer vision tasks. However, limited to the Gaussian imaging principle, there is not a thorough segmentation solution to the ambiguity in defocus and occlusion boundary areas. In this paper, we consider the essential element of image pixel, i.e., rays in the light space and propose ...
Hao Zhu 0005 +2 more
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Motion segmentation with occlusions on the superpixel graph
2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, 2009We present a motion segmentation algorithm that partitions the image plane into disjoint regions based on their parametric motion. It relies on a finer partitioning of the image domain into regions of uniform photometric properties, with motion segments made of unions of such “superpixels.” We exploit recent advances in combinatorial graph optimization
Alper Ayvaci, Stefano Soatto
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Hand segmentation with metric learning superpixels
2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP), 2014In this paper, we propose a novel method for hand segmentation. To improve the robustness to the wide range of hand appearances and illuminations, we segment the hand area with a superpixels based method instead of a general color model. With the exploitation of the distribution of hand pixels in color space, a distance metric learning stage is ...
Guangdong Hou +2 more
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Fast Superpixel Segmentation with Deep Features
2019In this paper, we propose a superpixel segmentation method which utilizes extracted deep features along with the combination of color and position information of the pixels. It is observed that the results can be improved significantly using better initial seed points.
Mubinun Awaisu +3 more
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Dynamic Random Walk for Superpixel Segmentation
2019In this paper, we present a novel Random Walk model called Dynamic Random Walk (DRW) for superpixel segmentation. The proposed DRW adds a new type of node called dynamic node to enrich the features of labels and reduce redundant calculation. By greedily optimizing the Weighted Random Walk Entropy (WRWE), our DRW can consider the features of both seed ...
Lei Zhu 0012 +3 more
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Edge Adaptive Seeding for Superpixel Segmentation
2017Finding a suitable seeding resolution when using superpixel segmentation methods is usually challenging. Different parts of the image contain different levels of clutter, resulting in an either too dense or too coarse segmentation. Since both possible solutions cause problems with respect to subsequent processing, we propose an edge adaptive seeding ...
Christian Wilms, Simone Frintrop
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Weakly-supervised semantic segmentation with superpixel guided local and global consistency
Pattern Recognition, 2022Sheng Yi, Xiang Wang, Tianyu Hu
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