3-D Imaging by Laser Radar and Applications in Preventing and Combating Crime and Terrorism

Abstract : This paper describes the ongoing research on 3-dimensional (3-D) imaging at FOI. Specifically, we address the new possibilities brought by laser radars, focusing on systems for high resolution 3-D imaging. 3-D laser radar is a viable technology in the effort to prevent and combat crime and terrorism. Real time 3-D sensing is a reality and can, besides more conventional techniques such as stereo vision and structured light, be achieved by range imaging. Current development of 3-D sensing flash imaging laser radars will provide the capability of high resolution 3-D imaging at long ranges with cm-resolution at full video rate. In all probability, this will revolutionize many applications, including law enforcement and forensic investigations. In contrast to conventional passive imaging systems, such as CCD and infrared (IR) techniques, laser radar provides both intensity and range information and has the ability to penetrate certain scene elements such as vegetation and windows. This, in turn, means new potentials, for example, in object recognition and identification and we address some of these new capabilities of 3-D laser radar systems. The results clearly show that 3-D imaging laser radar systems are useful in a variety of situations that can be used in the criminal justice system today to enable technologies for preventing and combating crime and terrorism.

[1]  H. Maas THE POTENTIAL OF HEIGHT TEXTURE MEASURES FOR THE SEGMENTATION OF AIRBORNE LASERSCANNER DATA , 1999 .

[2]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[3]  Dongmei Zhang,et al.  Harmonic maps and their applications in surface matching , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[4]  Lena M. Klasen Image sequence analysis of complex objects : law enforcement and defence applications , 2002 .

[5]  Roger Stettner,et al.  Eye-safe laser radar focal plane array for three-dimensional imaging , 2000, Defense, Security, and Sensing.

[6]  Asa Persson,et al.  Characterizing targets and backgrounds for 3D laser radars , 2004, SPIE Security + Defence.

[7]  Mikko Inkinen,et al.  A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners , 2001, IEEE Trans. Geosci. Remote. Sens..

[8]  Mathias Schardt,et al.  ASSESSMENT OF FOREST PARAMETERS BY MEANS OF LASER SCANNING , 2002 .

[9]  George Vosselman,et al.  COMPARISON OF FILTERING ALGORITHMS , 2003 .

[10]  Gyula Simon,et al.  Shooter localization in urban terrain , 2004, Computer.

[11]  George Vosselman,et al.  Two algorithms for extracting building models from raw laser altimetry data , 1999 .

[12]  J. Busck,et al.  Gated viewing and high-accuracy three-dimensional laser radar. , 2004, Applied optics.

[13]  George Vosselman,et al.  3D BUILDING MODEL RECONSTRUCTION FROM POINT CLOUDS AND GROUND PLANS , 2001 .

[14]  Christoph Hug,et al.  Extracting Artificial Surface Objects from Airborne Laser Scanner Data , 1997 .

[15]  M. Elmqvist GROUND SURFACE ESTIMATION FROM AIRBORNE LASER SCANNER DATA USING ACTIVE SHAPE MODELS , 2002 .

[16]  Milan Sonka,et al.  Image Processing, Analysis and Machine Vision , 1993, Springer US.

[17]  Richard M. Marino,et al.  Pose-independent automatic target detection and recognition using 3D LADAR data , 2004, SPIE Defense + Commercial Sensing.

[18]  Asa Persson,et al.  Methods for recognition of natural and man-made objects using laser radar data , 2004, SPIE Defense + Commercial Sensing.

[19]  Claus Brenner,et al.  RAPID PRODUCTION OF VIRTUAL REALITY CITY MODELS , 2000 .

[20]  Laurent D. Cohen,et al.  Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Åsa Persson,et al.  Detecting and measuring individual trees using an airborne laser scanner , 2002 .

[22]  Linda G. Shapiro,et al.  A new paradigm for recognizing 3-D objects from range data , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.