Summary
Real-time extraction of features from range images can play an important role in robotic vision tasks such as localisation and navigation. Feature driven segmentation of range images has been primarily used for 3D object recognition, and hence the accuracy of the detected features is a prominent issue. Feature extraction on range data has proven to be a more complex problem than on intensity images due to both the irregular distribution of range images. This paper presents a general approach to the development of scalable derivative operators using a finite element framework that can be applied directly to processing regularly or irregularly distributed range image data. The gradient operators of varying scales are evaluated with respect to their performance on regular and irregular grids.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abdou, I.E., Pratt, W.K.: Quantitative Design and Evaluation of Enhancement/ Threshold Edge Detectors. Proceedings of the IEEE 67(5) (1979)
Al-Hujazi, E., Sodd, A.: Range Image Segmentation with applications to Robot Bin-Picking Using Vacuum Gripper. IEEE Trans. Systems, Man, and Cybernetics 20(6) (1990)
Becker, E.B., Carey, G.F., Oden, J.T.: Finite Elements: An Introduction. Prentice Hall, London (1981)
Bellon, O.P., et al.: Edge Detection to Guide Range Image Segmentation by Clustering Techniques. In: IEEE Int. Conf. on Image Processing, Kobe, Japan (1999)
Bellon, O., Silva, L.: New Improvements on Range Image Segmentation by Edge Detection Techniques. In: Proceedings of the workshop on Artificial Intelligence and Computer Vision (2000)
Besl, P.J.: Active, optical range imaging sensors. Machine Vision and Apps 1, 127–152 (1988)
Cheng, J.-C., Don, H.-S.: Roof Edge Detection: A Morphological Skeleton Approach. In: Advances in Machine Vision: Strategies and Application, World Scientific, Singapore, pp. 171–191 (1992)
Coleman, S.A., Scotney, B.W., Suganthan, S.: Feature Extraction on Range Images - A New Approach. In: Coleman, S.A., Scotney, B.W., Suganthan, S. (eds.) Proceedings of IEEE International Conference on Robotics and Automation, Rome, pp. 1098–1103 (2007)
De Bakker, M.: The PSD chip, high speed acquisition of range images, PhD Thesis, Delft University of Technology (2000)
Dias, P., et al.: Combining Intensity and Range Images for 3D Modelling. In: Proceedings of the IEEE International Conference on Image Processing (ICIP 2003) (2003)
Flynn, P.J., Jain, A.K.: Three-dimensional object recognition. In: Handbook of Pattern Recognition and Image Processing: Computer Vision, pp. 497–541, Academic Press, San Diego (1994)
Franklin, D., Firby, R.J.: Integrating Range and Object Data for Robot Navigation. In: Proceedings of the first international conference on Autonomous agents,Marina del Rey, California, United States, pp. 185–192 (1997)
Huber, D., Carmichael, O., Hebert, M.: 3-D Map Reconstruction from Range Data, In:Proc. of the IEEE Inter. In: Conf. on Robotics & Automation, San Francisco, CA, pp. 891–897 (2000)
Jarvis, R.A.: Range Sensing for Computer Vision. In: Three-Dimensional Object Recognition Systems, pp. 17–56. Elsevier Science, Amsterdam (1993)
Jiang, X.Y., Bunke, H.: Edge detection in range image based on scan line approximation. Computer Vision ad Image Understanding 73(2), 183–199 (1999)
Jiang, X.Y., Bunke, H.: Fast Segmentation of Range Images into Planar Regions by Scan Line Grouping. Machine Vision and Applications 7(2), 115–122 (1994)
Kaveti, S., et al.: Second-Order Implicit Polynomials for segmentation of Range Images. Pattern Recognition 29(6), 937–949 (1996)
Krishnapuram, R., Gupta, S.: Morphological Methods for Detection and Classification for Edges in Range Images. Journal of Mathematical Imaging Vision, 351–375 (1992)
Neira, J., Tardos, J.D., Horn, J., Schmidt, G.: Fusing Range and Intensity Images for Mobile Robot Localization. IEEE Transactions on Robotics and Automation 15(1), 76–84 (1999)
Newman, T.S., Jain, A.K.: A system for 3D CAD-based inspection using range images. Pattern Recognition 28(10), 1555–1574 (1995)
Parvin, B., Medioni, G.: Adaptive Multiscale Feature Extraction From Range Data. Computer Vision Graphics, Image Understanding 45, 346–356 (1989)
Sabata, B., Aggarwal, J.K.: Surface correspondence and motion computation from a pair of range images. Computer Vision and Image Understanding 63, 232–250 (1996)
Sappa, A.D., Devy, M.: Fast Range Image Segmentation by an Edge Detection Strategy. In: Proc 3rd Int. Conference on 3D Digital Imaging and Modelling, Quebec, Canada, pp. 292–299 (2001)
Trucco, E., Fisher, R.B.: Experiments in Curvature-Based Segmentation of Range Data. IEEE Trans. Pattern Analysis and Machine Intelligence 17(2), 177–182 (1995)
Umeda, K., Arai, T.: Industrial Vision System by Fusing Range image and Intensity Image. Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 337–344 (1994)
Zhao, D., Li, S.: A 3D image processing method for manufacturing process automation. In: Computer in Industry, vol. 56, pp. 975–985. Elsevier, Amsterdam (2005)
http://sampl.eng.ohio-state.edu/~sampl/data/3DDB/RID/-index.htm
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Suganthan, S., Coleman, S., Scotney, B. (2008). Scalable Operators for Feature Extraction on 3-D Data. In: Bruyninckx, H., Přeučil, L., Kulich, M. (eds) European Robotics Symposium 2008. Springer Tracts in Advanced Robotics, vol 44. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78317-6_27
Download citation
DOI: https://doi.org/10.1007/978-3-540-78317-6_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78315-2
Online ISBN: 978-3-540-78317-6
eBook Packages: EngineeringEngineering (R0)