Pan, XiaoZhou, YuanfengLiu, ShuweiZhang, CaimingStam, Jos and Mitra, Niloy J. and Xu, Kun2015-10-072015-10-072015978-3-905674-96-5https://doi.org/10.2312/pg.20151284A 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.I.3.3 [Computer Graphics]Picture/Image GenerationLine and curve generationSuperpixels Generation of RGB-D Images Based on Geodesic Distance10.2312/pg.2015128471-76