Automatic superpixel generation algorithm based on a quadric error metric in 3D space

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• 作者：Yongxia Zhang ; Long Ma ; Yuanfeng Zhou ; Caiming Zhang
• 关键词：Triangle mesh ; Mesh simplification ; Image segmentation ; Quadric error metric
• 刊名：Signal, Image and Video Processing
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：11
• 期：3
• 页码：471-478
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Signal,Image and Speech Processing; Image Processing and Computer Vision; Computer Imaging, Vision, Pattern Recognition and Graphics; Multimedia Information Systems;
• 出版者：Springer London
• ISSN：1863-1711
• 卷排序：11

文摘

As a preprocessing step for computer vision tasks, research on generating superpixels of an image has been widely conducted recently. In this paper, we propose a fully automatic superpixel generation algorithm by simplifying the 3D triangle mesh modeled from a 2D input image. The simplification is performed based on a modified quadric error metric (QEM) method. The pipeline of our algorithm is simple. Given an image, we first turn it into a 2D triangle mesh and then lift the mesh to 3D based on the gray values of the image. We then simplify the 3D mesh based on the modified QEM method which encodes the features in the image intrinsically to ensure feature-aware superpixels. After obtaining the simplified mesh, we map it back to the 2D image to generate triangular-shaped superpixels. Our algorithm is fully automatic. The number of superpixels can be controlled intuitively. Experimental results demonstrate the effectiveness of our approach.