Abstract
Solving the next best view (NBV) problem is an important task for automated 3D reconstruction. An NBV algorithm provides sensor positions, from which maximal information gain about the measurement object during the next scan can be expected. With no or limited information available during the first views, automatic data driven view planning performs suboptimal. In order to overcome these inefficiencies during startup phase, we examined the use of time-of-flight (TOF) camera data to improve view planning. The additional low resolution 3D information, gathered during sensor movement, allows to plan even the first scans customized to previously unknown objects. Measurement examples using a robot mounted fringe projection stereo 3D scanner with a TOF camera are presented.
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References
Low, K.L., Lastra, A.: An Adaptive Hierarchical Next-Best-View Algorithm for 3D Reconstruction of Indoor Scenes. In: 14th Pacific Conference on Computer Graphics and Applications (October 2006)
Cowan, C.K., Kovesi, P.D.: Automatic sensor placement from vision task requirements. IEEE Trans. Pattern Anal. Machine Intell. 10, 407–416 (1988)
Massios, N.A., Fisher, R.B.: A Best Next View selection algorithm incorporating a quality criterion. In: 9th BMVC, September 1998, pp. 780–789 (1998)
Banta, J.E., Abidi, M.A.: Autonomous placement of a range sensor for acquisition of optimal 3-D models. In: 22nd IEEE International Conference on Industrial Electronics, Control, and Instrumentation, vol. 3, pp. 1583–1588 (1996)
Prusak, A., Melnychuk, O., Roth, H., Schiller, I., Koch, R.: Pose estimation and map building with a Time-Of-Flight-camera for robot navigation. Intern. Journ. of Intelligent Systems Technologies and Applications 5(3/4), 355–364 (2008)
Pito, R.: A Solution to the Next Best View Problem for Automated Surface Acquisition. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(10), 1016–1030 (1999)
Chen, S.Y., Li, Y.F.: Vision Sensor Planning for 3D Model Acquisition. IEEE Transactions on Systems, Man and Cybernetics – B 35(5), 894–904 (2005)
Li, Y.F., Liu, Z.G.: Information Entropy-Based Viewpoint Planning for 3-D Object Reconstruction. IEEE Transactions on Robotics 21(3), 324–337 (2005)
Wenhardt, S., Deutsch, B., Hornegger, J., Niemann, H., Denzler, J.: An Information Theoretic Approach for Next Best View Planning in 3-D Reconstruction. In: 18th International Conference on Pattern Recognition, 2006. ICPR 2006, vol. 1, pp. 103–106 (2006)
Hernandez, C., Vogiatzis, G., Cipolla, R.: Probabilistic visibility for multi-view stereo. In: IEEE Conference on Computer Vision and Pattern Recognition, 2007. CVPR 2007, June 17-22, 2007, pp. 1–8 (2007)
Creath, K.: Temporal Phase Measurement Methods. In: Interferogram Analysis – Digital Fringe Pattern Measurement Techniques, pp. 94–140. Institute of Physics Publishing (1993)
Curless, B., Levoy, M.: A Volumetric Method for Building Complex Models from Range Images. In: Proceedings of SIGGRAPH 1996, pp. 303–312. ACM Press, New York (1996)
Munkelt, C., Kuehmstedt, P., Denzler, J.: Incorporation of a-priori information in planning the next best view. In: Kobbelt, L., Kuhlen, T., Aach, T., Westermann, R. (eds.) Vision, Modeling, and Visualization 2006, pp. 261–268 (2006)
Munkelt, C., Trummer, M., Denzler, J., Wenhardt, S.: Benchmarking 3D Reconstructions from Next Best View Planning. In: Proceedings of IAPR Conference on Machine Vision Applications, May 2007, pp. 552–555 (2007)
Kühmstedt, P., Munkelt, C., Heinze, M., Bräuer-Burchardt, C., Notni, G.: 3D shape measurement with phase correlation based fringe projection. In: Optical Measurement Systems for Industrial Inspection V, vol. 6616, p. 66160B. SPIE (2007)
PMDTechnologies GmbH: PMD [vision] O3 Datasheet (2007), http://www.pmdtec.com/e_inhalt/documents/datasheet_O3_v0100.pdf
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Munkelt, C., Trummer, M., Kühmstedt, P., Notni, G., Denzler, J. (2009). View Planning for 3D Reconstruction Using Time-of-Flight Camera Data. In: Denzler, J., Notni, G., Süße, H. (eds) Pattern Recognition. DAGM 2009. Lecture Notes in Computer Science, vol 5748. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03798-6_36
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DOI: https://doi.org/10.1007/978-3-642-03798-6_36
Publisher Name: Springer, Berlin, Heidelberg
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