Pixel-Line Based Clustering for the 3D Point Cloud Generated by Kinect Depth Map

被引:0
作者
Qiu, Quan [1 ]
Zheng, Wengang [1 ]
机构
[1] Beijing Res Ctr Intelligent Equipment Agr, Dept Agr Automat, Beijing 100097, Peoples R China
来源
2013 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION (ICIA) | 2013年
关键词
clustering; pixel-line based; 3D point cloud; Kinect; depth image;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A novel pixel-line based clustering algorithm for Kinect depth image data is proposed in this paper. The algorithm first clusters the three-dimensional points belonging to the same pixel row. Then the single row clusters coming from adjacent rows are compared and matched to fulfill the three-dimensional cluster growth. Experiments are carried out with both office scene and greenhouse scene. The clustering results show that the algorithm is good at highlighting small objects but is sensitive to uneven surfaces.
引用
收藏
页码:705 / 710
页数:6
相关论文
共 13 条
[1]  
[Anonymous], IEEERAS INT C HUM RO
[2]  
Douillard B, 2011, IEEE INT CONF ROBOT
[3]   RANDOM SAMPLE CONSENSUS - A PARADIGM FOR MODEL-FITTING WITH APPLICATIONS TO IMAGE-ANALYSIS AND AUTOMATED CARTOGRAPHY [J].
FISCHLER, MA ;
BOLLES, RC .
COMMUNICATIONS OF THE ACM, 1981, 24 (06) :381-395
[4]  
Fouhey DF, 2012, LECT NOTES COMPUT SC, V7584, P83, DOI 10.1007/978-3-642-33868-7_9
[5]  
Goron LucianCosmin., 2012, Robotics
[6]  
Proceedings of ROBOTIK 2012
[7]  
7th German Conference on, P1
[8]  
Holz Dirk, 2012, RoboCup 2011: Robot Soccer World Cup XV: LNCS 7416, P306, DOI 10.1007/978-3-642-32060-6_26
[9]   Binocular Stereo Vision Based Obstacle Avoidance Algorithm for Autonomous Mobile Robots [J].
Kumar, Saurav .
2009 IEEE INTERNATIONAL ADVANCE COMPUTING CONFERENCE, VOLS 1-3, 2009, :254-+
[10]   Using Segmented 3D Point Clouds for Accurate Likelihood Approximation in Human Pose Tracking [J].
Lehment, Nicolas ;
Kaiser, Moritz ;
Rigoll, Gerhard .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2013, 101 (03) :482-497