Finding organized structures in 3-D ladar data

In this paper, we address the problem of finding organized thin structures in three-dimensional (3-D) data. Linear and planar structures segmentation received much attention but thin structures organized in complex patterns remain a challenge for segmentation algorithms. We are interested especially in the problems posed by repetitive and symmetric structures acquired with a laser range finder. The method relies on 3-D data projections along specific directions and 2-D histograms comparison. The sensitivity of the classification algorithm to the parameter settings is evaluated and a segmentation method proposed. We illustrate our approach with data from a concertina wire in terrain with vegetation.

[1]  Martial Hebert,et al.  Analysis and Removal of Artifacts in 3-D LADAR Data , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[2]  Nicolas Vandapel,et al.  Toward laser pulse waveform analysis for scene interpretation , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[3]  Martial Hebert,et al.  Natural terrain classification using 3-d ladar data , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[4]  Yanxi Liu,et al.  A computational model for periodic pattern perception based on frieze and wallpaper groups , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Leonidas J. Guibas,et al.  The Earth Mover's Distance as a Metric for Image Retrieval , 2000, International Journal of Computer Vision.

[6]  Martial Hebert,et al.  Robust extraction of multiple structures from non-uniformly sampled data , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[7]  Larry H. Matthies,et al.  Foliage discrimination using a rotating ladar , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[8]  Mark Ollis,et al.  Structural method for obstacle detection and terrain classification , 2003, SPIE Defense + Commercial Sensing.

[9]  Goran Forssell Passive IR polarization measurements applied to covered surface landmines , 2003, SPIE Defense + Commercial Sensing.

[10]  Martial Hebert,et al.  Experimental Results in Using Aerial LADAR Data for Mobile Robot Navigation , 2003, FSR.

[11]  Anthony Stentz,et al.  Learning Predictions of the Load-Bearing Surface for Autonomous Rough-Terrain Navigation in Vegetation , 2003, FSR.

[12]  Alonzo Kelly,et al.  Real-Time, Multi-Perspective Perception for Unmanned Ground Vehicles , 2003 .

[13]  Karl R. Schulz,et al.  Hellas: obstacle warning system for helicopters , 2002, SPIE Defense + Commercial Sensing.

[14]  Karl Murphy,et al.  Autonomous Mobility for the Demo III Experimental Unmanned Vehicles , 2002 .

[15]  Roberto Manduchi,et al.  Fast and reliable obstacle detection and segmentation for cross-country navigation , 2002, Intelligent Vehicle Symposium, 2002. IEEE.

[16]  Bernard Chazelle,et al.  A Reflective Symmetry Descriptor , 2002, ECCV.

[17]  Martin David Adams,et al.  On-line gradient based surface discontinuity detection for outdoor scanning range sensors , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[18]  Kelly D. Sherbondy,et al.  Eyesafe laser-illuminated tripwire (ELIT) detector , 2001, SPIE Defense + Commercial Sensing.

[19]  Carlo Tomasi,et al.  The Earth Mover’s Distance , 2001 .

[20]  David Mumford,et al.  Statistics of range images , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[21]  Mi-Suen Lee,et al.  A Computational Framework for Segmentation and Grouping , 2000 .

[22]  George D. Stetten,et al.  Medical Node Models to Identify and Measure Objects in Real-Time 3D Echocardiography , 1999, IEEE Trans. Medical Imaging.

[23]  J. Alison Noble,et al.  Statistical 3D Vessel Segmentation Using a Rician Distribution , 1999, MICCAI.

[24]  Bradley T. Blume,et al.  Range imaging for underwater vision enhancement , 1999, Defense, Security, and Sensing.

[25]  Yong-Hoon Kim,et al.  Multi-wire detection and image reconstruction using 27 GHz ISAR , 1999, IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293).

[26]  Dinggang Shen,et al.  Symmetry Detection by Generalized Complex (GC) Moments: A Close-Form Solution , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  K. Yamada,et al.  Analysis of the infrared images to detect power lines , 1997, TENCON '97 Brisbane - Australia. Proceedings of IEEE TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications (Cat. No.97CH36162).

[28]  Changming Sun,et al.  3D Symmetry Detection Using The Extended Gaussian Image , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[29]  Andrew E. Johnson,et al.  Spin-Images: A Representation for 3-D Surface Matching , 1997 .