|
| This Article | ||
| ||
| Share | ||
| Bibliographic References | ||
| Add to: | ||
 Digg  Furl  Spurl  Blink  Simpy  Google  Del.icio.us  Y!MyWeb | ||
| Search | ||
| ASCII Text | x | ||
| "An Experimental Comparison of Range Image Segmentation Algorithms," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 7, pp. 673-689, July, 1996. | |||
| BibTex | x | ||
| @article{ 10.1109/34.506791, author = {}, title = {An Experimental Comparison of Range Image Segmentation Algorithms}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {18}, number = {7}, issn = {0162-8828}, year = {1996}, pages = {673-689}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.506791}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - An Experimental Comparison of Range Image Segmentation Algorithms IS - 7 SN - 0162-8828 SP673 EP689 EPD - 673-689 PY - 1996 KW - Experimental comparison of algorithms KW - range image segmentation KW - low level processing KW - performance evaluation. VL - 18 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
Abstract—A methodology for evaluating range image segmentation algorithms is proposed. This methodology involves 1) a common set of 40 laser range finder images and 40 structured light scanner images that have manually specified ground truth and 2) a set of defined performance metrics for instances of correctly segmented, missed, and noise regions, over- and under-segmentation, and accuracy of the recovered geometry. A tool is used to objectively compare a machine generated segmentation against the specified ground truth. Four research groups have contributed to evaluate their own algorithm for segmenting a range image into planar patches.
[1] D.H. Ballard and C.M. Brown, Computer Vision, Prentice Hall, Upper Saddle River, N.J., 1982.
[2] J.L. Barron, D.J. Fleet, and S.S. Beauchemin, “Performance of Optical Flow Techniques,” Int'l J. Computer Vision, vol. 12, no. 1, pp. 43–77, 1994.
[3] P. Besl, “Active, Optical Imaging Sensors,” Machine Vision and Applications, pp. 127-152, 1988.
[4] P.J. Besl and R.C. Jain,“Segmentation through variable-order surface fitting,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 10, no. 2, pp. 167-191, Mar. 1988.
[5] S.M Bhandarkar and A. Siebert, "INTEGRA—An Integrated System for Range Image Understanding," Int'l J. Pattern Recognition and Artificial Intelligence, vol. 6, no. 5, pp. 913-953, 1992.
[6] R.C. Bolles, H.H. Baker, and M.J. Hannah, "The JISCT Stereo Evaluation," Proc. Image Understanding Workshop, pp. 263-274,Washington, D.C., 1993.
[7] K.L. Boyer, M.J. Mirza, and G. Ganguly, "The Robust Sequential Estimator: A General Approach and Its Application to Surface Organization in Range Data," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, no. 10, pp. 987-1,001, Oct. 1994.
[8] R.O. Duda and P.E. Hart, Pattern Classification and Scene Analysis.New York: John Wiley&Sons, 1973.
[9] A.W. Fitzgibbon, D.W. Eggert, and R.B. Fisher, "High-level CAD Model Acquisition from Range Images," technical report, Dept. of Artificial Intelligence, Univ. of Edinburgh, 1995.
[10] P.J. Flynn and A.K. Jain, Surface classification: Hypothesis Testing and Parameter Estimation Proc. Computer Vision and Pattern Recognition, 1988.
[11] P. Flynn and A. Jain, "BONSAI: 3D object recognition using constrained search," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, pp. 1066-1075, 1991.
[12] S. Ghosal and R. Mehrotra, "Segmentation of Range Images: An Orthogonal Moment-Based Integrated Approach," IEEE Trans. Robotics and Automation, vol. 9, pp. 385-389, 1993.
[13] D.B. Goldgof, T.S. Huang, and H. Lee, "A Curvature-Based Approach to Terrain Recognition," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, 1,213-1,217, 1989.
[14] R.C. Gonzalez and R.E. Woods, Digital Image Processing, Addison-Wesley, New York, 1993.
[15] R.M. Haralick and L.G. Shapiro, Computer and Robot Vision. New York: Addison-Wesley, 1993.
[16] R. Haralick, “Performance Characterization in Image Analysis: Thinning, a Case in Point,” Pattern Recognition Letters, vol. 13, pp. 5-12, 1992.
[17] R. Hoffman and A.K. Jain,“Segmentation and classification of range images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, no.5, pp. 608-620, Sept. 1987.
[18] A.K. Jain and R.C. Dubes, Algorithms for Clustering Data. Englewood Cliffs, N.J.: Prentice Hall, 1988.
[19] R.C. Jain,A.K. Jain,Analysis and Interpretation of Range Images,New York: Springer-Verlag, 1990.
[20] R.C. Jain and T.O. Binford, "Ignorance, Myopia, and Naivete in Computer Vision Systems," CVGIP, vol. 53-1, pp. 112-117, 1991.
[21] R.A. Jarvis, "Three Dimensional Object Recognition Systems," Range Sensing for Computer Vision, A.K. Jain and P.J. Flynn, eds., pp. 17-56. Elsevier Science Publishers, 1993.
[22] X.Y. Jiang and H. Bunke, "Fast Segmentation of Range Images into Planar Regions by Scan Line Grouping," Machine Vision and Applications, vol. 7, no. 2, pp. 115-122, 1994.
[23] R. Krishnapuram and S. Gupta, "Morphological Methods for Detection and Classification of Edges in Range Images," Mathematical Imaging and Vision, vol. 2, pp. 351-375, 1992.
[24] S.M. Lavalle and S.A. Hutchinson, “A Bayesian Segmentation Methodology for Parametric Image Models,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, pp. 211-217, 1995.
[25] S.U. Lee, S.Y. Chung, and R.H. Park, “A Comparative Performance Study of Several Global Thresholding Techniques for Segmentation,” Computer Vision, Graphics, and Image Processing, vol. 52, pp. 171-190, 1990.
[26] M.D. Levine and A.M. Nazif, "An Experimental Rule Based System for Testing Low Level Segmentation Strategies," Multicomputers and Image Processing: Algorithms and Programs, K. Preston and L. Uhr, eds., pp.149-160. Academic Press, 1982.
[27] M.D. Levine, Vision in Man and Machine.New York: McGraw-Hill, 1985.
[28] G.W. Cottrell and M.K. Fleming, "Categorisation of Faces Using Unsupervised Feature Extraction," Proc. Int'l Conf. Neural Networks,San Diego, vol. 2, pp. 65-70, 1990.
[29] Y.W. Lim and S.U. Lee, "On the Color Image Segmentation Algorithm Based on the Thresholding and the Fuzzy C-Means Techniques," Pattern Recognition, vol. 23, no. 9, pp. 935-952, 1990.
[30] S.-P. Liou, A.H. Chiu, and R.C. Jain, “A Parallel Technique for Signal-Level Perceptual Organization,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, no. 4, pp. 317-325, Apr. 1991.
[31] T.S. Newman, P.J. Flynn, and A.K. Jain, “Model-Based Classification of Quadric Surfaces,” CVGIP: Image Understanding, vol. 58, no. 2, pp 235-249, 1993.
[32] N. Pal and S. Pal, "A Review on Image Segmentation Techniques," Pattern Recognition, vol. 26, no. 9, pp. 1,277-1,294, 1993.
[33] Perceptron Inc., LASAR Hardware Manual, 23855 Research Drive, Farmington Hills, Michigan, 1993.
[34] K. Price, "Anything You Can Do, I Can Do Better (No You Can't)..." CVGIP, vol. 36, pp. 387-391, 1986.
[35] B. Sabata,F. Arman,, and J.K. Aggarwal, Segmentation of 3D range images using pyramidal data structures. “, Computer Vision, Graphics, and Image Processing, vol. 57, pp. 373-387, May 1993.
[36] T.G. Stahs and F.M. Wahl, "Fast and Robust Range Data Acquisition in a Low-Cost Environment," SPIE #1395: Close-Range Photogrammetry Meets Machine Vision, pp. 496-503,Zurich, 1990.
[37] R.W. Taylor, M. Savini, and A.P. Reeves, "Fast Segmentation of Range Imagery into Planar Regions," Computer Vision, Graphics, and Image Processing, vol. 45, no. 1, pp. 42-60, 1989.
[38] E. Trucco and R.B. Fisher, "Experiments in Curvature-Based Segmentation of Range Data," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 2, pp. 177-181, Feb. 1995.
[39] M.A. Wani and B.G. Batchelor, “Edge-Region-Based Segmentation of Range Images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, no. 3, pp. 314-319, Mar. 1994.
[40] N. Yokoya and M. Levine,“Range image segmentation based on differential geometry: a hybrid approach,” IEEE Trans. on PAMI, vol. 11, no. 6, pp. 643-649, Jun. 1989.
[41] Handbook of Pattern Recognition and Image Processing: Computer Vision, T.Y. Young, ed., Chapter 7. Academic Press, 1994.
[42] X. Yu, T.D. Bui, and A. Krzyzak, "Robust Estimation for Range Image Segmentation and Reconstruction," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, no. 5, pp. 530-538, May 1994.
[43] R. Zhang, P.S. Tsai, J.E. Cryer, and M. Shah, "Analysis of Shape From Shading Techniques," Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition, pp. 377-384, 1994.