A Solution to the Next Best View Problem for Automated Surface Acquisition

A solution to the "next best view" (NBV) problem for automated surface acquisition is presented. The NBV problem is to determine which areas of a scanner's viewing volume need to be scanned to sample all of the visible surfaces of an a priori unknown object and where to position/control the scanner to sample them. A method for determining the unscanned areas of the viewing volume is presented. In addition, a novel representation, positional space, is presented which facilitates a solution to the NBV problem by representing what must be and what can be scanned in a single data structure. The number of costly computations needed to determine if an area of the viewing volume would be occluded from some scanning position is decoupled from the number of positions considered for the NBV, thus reducing the computational cost of choosing one. An automated surface acquisition systems designed to scan all visible surfaces of an a priori unknown object is demonstrated on real objects.

[1]  Andrew Blake,et al.  Real-time Visual Tracking for Surveillance and Path Planning , 1992, ECCV.

[2]  Richard Pito,et al.  A sensor-based solution to the "next best view" problem , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[3]  Glenn H. Tarbox,et al.  IVIS: An Integrated Volumetric Inspection System , 1995, Comput. Vis. Image Underst..

[4]  Glenn H. Tarbox,et al.  Planning for Complete Sensor Coverage in Inspection , 1995, Comput. Vis. Image Underst..

[5]  Richard Anthony Pito Automated surface acquisition using range cameras , 1997 .

[6]  Mongi A. Abidi,et al.  Best-next-view algorithm for three-dimensional scene reconstruction using range images , 1995, Other Conferences.

[7]  Konstantinos A. Tarabanis,et al.  A survey of sensor planning in computer vision , 1995, IEEE Trans. Robotics Autom..

[8]  Avinash C. Kak,et al.  Planning sensing strategies in a robot work cell with multi-sensor capabilities , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[9]  R. Bajcsy Active perception , 1988 .

[10]  John K. Tsotsos,et al.  Active object recognition , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[11]  Frank P. Ferrie,et al.  Autonomous exploration: driven by uncertainty , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[12]  Marc Levoy,et al.  Zippered polygon meshes from range images , 1994, SIGGRAPH.

[13]  Y. J. Tejwani,et al.  Robot vision , 1989, IEEE International Symposium on Circuits and Systems,.

[14]  Colin Bradley,et al.  Automated laser scanning based on orthogonal cross sections , 1996 .

[15]  S. M. Wu,et al.  Dynamic calibration and compensation of a 3D laser radar scanning system , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[16]  Roger Y. Tsai,et al.  Analytical characterization of the feature detectability constraints of resolution, focus, and field-of-view for vision sensor planning , 1994 .

[17]  Xiaobu Yuan,et al.  A Mechanism of Automatic 3D Object Modeling , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  In So Kweon,et al.  Experimental Characterization of the Perceptron Laser Rangefinder , 1991 .

[19]  Hongbin Zha,et al.  Active modeling of 3-D objects: planning on the next best pose (NBP) for acquiring range images , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[20]  Lambert E. Wixson,et al.  Viewpoint selection for visual search , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[21]  Gérard G. Medioni,et al.  Object modeling by registration of multiple range images , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[22]  Dimitri Papadopoulos-Orfanos,et al.  Automatic 3-D digitization using a laser rangefinder with a small field of view , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[23]  Katsushi Ikeuchi,et al.  Task-oriented generation of visual sensing strategies , 1995, Proceedings of IEEE International Conference on Computer Vision.

[24]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[25]  Konstantinos A. Tarabanis,et al.  Computing Occlusion-Free Viewpoints , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Samia Boukir,et al.  Structure From Controlled Motion , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Y. D. Chen,et al.  Dynamic calibration and compensation of a 3D laser radar scanning system , 1993, IEEE Trans. Robotics Autom..

[28]  Nikolaos Papanikolopoulos,et al.  Computation of shape through controlled active exploration , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[29]  Gérard G. Medioni,et al.  Object modelling by registration of multiple range images , 1992, Image Vis. Comput..

[30]  Kiriakos N. Kutulakos,et al.  Global surface reconstruction by purposive control of observer motion , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[31]  Adrian Hilton,et al.  Marching triangles: range image fusion for complex object modelling , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[32]  Katsushi Ikeuchi,et al.  Task-Oriented Generation of Visual Sensing Strategies , 1996 .

[33]  Ruzena Bajcsy,et al.  Occlusions as a Guide for Planning the Next View , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  William E. Lorensen,et al.  Decimation of triangle meshes , 1992, SIGGRAPH.

[35]  Marc Levoy,et al.  Light field rendering , 1996, SIGGRAPH.

[36]  Ruzena Bajcsy,et al.  Solution to the next best view problem for automated CAD model acquisiton of free-form objects using range cameras , 1995, Optics East.

[37]  Marc Levoy,et al.  A volumetric method for building complex models from range images , 1996, SIGGRAPH.

[38]  Takeo Kanade,et al.  Sensor placement design for object pose determination with three light-stripe range finders , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[39]  Robert Bergevin,et al.  Towards a General Multi-View Registration Technique , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[40]  Ioannis Stamos,et al.  3-D modeling from range imagery: an incremental method with a planning component , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[41]  Peter Kovesi,et al.  Automatic Sensor Placement from Vision Task Requirements , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[42]  A. David Marshall,et al.  Automatically planning the inspection of three-dimensional objects using stereo computer vision , 1996, Other Conferences.

[43]  Richard Pito,et al.  Mesh integration based on co-measurements , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[44]  C. Ian Connolly,et al.  The determination of next best views , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[45]  Martin Rutishauser,et al.  Merging range images of arbitrarily shaped objects , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[46]  Éric Marchand,et al.  Controlled camera motions for scene reconstruction and exploration , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[47]  Richard Pito A registration aid , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[48]  J. Kahn,et al.  Traditional Galleries Require Fewer Watchmen , 1983 .

[49]  Martial Hebert,et al.  A system for semi-automatic modeling of complex environments , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[50]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[51]  M.J. Daily,et al.  An operational perception system for cross-country navigation , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[52]  Kiriakos N. Kutulakos,et al.  Global Surface Reconstruction by Purposive Control of Observer Motion , 1995, Artif. Intell..