.png){kind=icon}
返回
Spherical Superpixel Segmentation
.png){kind=icon}
PRE
AI
DOI：10.1109/TMM.2017.2772842.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
These days, superpixel algorithms are widely used in computer vision and multimedia applications. However, existing algorithms are designed for planar images, which are less suited to deal with wide angle images. In this paper, we present a superpixel segmentation method for 360 degrees spherical images. Unlike previous methods, our approach explicitly considers the geometry for spherical images and makes clustering to spherical image pixels. It starts with the seeds defined by Hammersley points sampled on the sphere, then iterates between assignment step and update step, which are both based on the distance metric respecting spherical geometry. We evaluate our method on the transformed Berkeley segmentation dataset and panorama segmentation dataset collected by ourselves. Experimental results show that our method can gain better performance in terms of adherence to image boundaries and superpixel structural regularity. Furthermore, superpixels generated by our method can reserve the coherence across image boundaries and all have closed contours.
Keyword:
Superpixel
segmentation
spherical image
panorama
clustering
Hammersley
SLIC
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.7
论文数:
5.2K
被引数:
2.4W
机构
引用论文
Effect of 22R-hydroxycholesterol on the action of sphingomyelinase from Bacillus cereus toward bovine erythrocytes.png)
Toxicon
ToxiconIF0
PREAI
分享收藏分享收藏
查看更多内容