Kinect Depth Data Segmentation Based on Gauss Mixture Model Clustering
Indoor scene understanding based on the depth image data is a cutting-edge issue in the field of three-dimensional computer vision.Taking the layout characteristics of the indoor scenes and more plane features in these scenes into account,this paper presents a depth image segmentation method based on Gauss Mixture Model clustering.First,transform the Kinect depth image data into point cloud which is in the form of discrete three-dimensional point data,and denoise and down-sample the point cloud data; second,calculate the point normal of all points in the entire point cloud,then cluster the entire normal using Gaussian Mixture Model,and finally implement the entire point clouds segmentation by RANSAC algorithm.Experimental results show that the divided regions have obvious boundaries and segmentation quality is above normal,and lay a good foundation for object recognition.
indoor scene understanding depth data segmentation Gauss Mixture Model RANSAC algorithm Kinect
Tingwei DU Bo LIU
College of Computer Science,Beijing University Of Technology,Beijing,100124,China
国际会议
郑州
英文
1854-1858
2013-10-19(万方平台首次上网日期,不代表论文的发表时间)