Superpixels Generation of RGB-D Images Based on Geodesic Distance

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Date
2015
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
A novel algorithm for generating superpixels of RGB-D images is presented in this paper. A regular triangular mesh is constructed by the depth and a local geometric features sensitive initialization method is proposed for initializing seeds by a density function. Over-segmentation of the vertices on mesh can be generated by minimizing a new energy function defined by weighted geodesic distance which can be used for measuring the similarity of vertices with color information. At last, superpixels are generated by re-mapping the mesh over-segmentation to 2D image. During energy optimizing, we will check the topology correctness of the superpixels and refine the topology of the superpixels. Experiments on a large RGB-D images database show that the superpixels generated by the new method can adhere to the object boundaries well and outperform the state-of-the-art methods.
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@inproceedings{
10.2312:pg.20151284
, booktitle = {
Pacific Graphics Short Papers
}, editor = {
Stam, Jos and Mitra, Niloy J. and Xu, Kun
}, title = {{
Superpixels Generation of RGB-D Images Based on Geodesic Distance
}}, author = {
Pan, Xiao
and
Zhou, Yuanfeng
and
Liu, Shuwei
and
Zhang, Caiming
}, year = {
2015
}, publisher = {
The Eurographics Association
}, ISBN = {
978-3-905674-96-5
}, DOI = {
10.2312/pg.20151284
} }
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