Rapid object indexing using locality sensitive hashing and joint 3D-signature space estimation

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 28, Issue 7, 2006, Pages 1111-1126

  Matei, Bogdan ^a   Huber, Daniel ^b   Hebert, Martial ^b   Tan, Yi ^a   Kumar, Rakesh ^a  

^a SARNOFF CORPORATION   (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

approximate nearest neighbor; hashing; indexing; pose estimation; Three dimensional object recognition

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CAR; COMPUTER ASSISTED DIAGNOSIS; FACTUAL DATABASE; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; ONLINE SYSTEM; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; AUTOMOBILES; DATABASES, FACTUAL; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; ONLINE SYSTEMS; PATTERN RECOGNITION, AUTOMATED;

EID: 33746428114     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2006.148     Document Type: Article

References (40)

1. K. Arun, T. Huang, and S. Blostein, “Least-Squares Fitting of Two 3D Point Sets,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, pp. 698–700, 1987.
2. M. Bawa, T. Condie, and P. Ganesan, “LSH Forest: Self-Tuning Indexes for Similarity Search,” Proc. 14th Int'l Conf. World Wide Web, pp. 651–660, 2005.
3. P. Besl and N. McKay, “A Method for Registration of 3D Shapes,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, pp. 540–547, 1992.
4. R. Campbell and P. Flynn, “A Survey of Free-Form Object Representation and Recognition Techniques,” Computer Vision and Image Understanding, vol. 81, pp. 166–210, 2001.
5. C.-S. Chen, Y.-P. Hung, and J.-B. Cheng, “Ransac-Based DARCES: A New Approach to Fast Automatic Registration of Partially Overlapping Range Images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 10, pp. 1229–1234, Oct. 1999.
6. C.-S. Chua and R. Jarvis, “Point Signatures: A New Representation for 3D Object Recognition,” Int'l J. Computer Vision, vol. 25, no. 1, pp. 63–85, 1997.
7. M. de Berg, M. van Kreveld, M. Overmars, and O. Schwarzkopf, Computational Geometry. Springer, 2000.
8. H. Delingette, M. Hebert, and K. Ikeuchi, “A Sperical Representation for the Recognition of Curved Objects,” Computer Vision and Pattern Recognition, pp. 103–112, May 1993.
9. C. Dorai and A. Jain, “Cosmos—A Representation Scheme for 3D Free-Form Objects,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, pp. 1115–1130, 1997.
10. M. Fischler and R. Bolles, “Random Sample Consensus: A Paradigm for Model Fitting with Application to Image Analysis and Automated Cartography,” Comm. ACM, vol. 24, pp. 381–395, 1981.
11. A. Frome, D. Huber, R. Kolluri, T. Bulow, and J. Malik, “Recognizing Objects in Range Data Using Regional Point Descriptors,” Proc. European Conf. Computer Vision, May 2004.
12. B. Georgescu, I. Shimshoni, and P. Meer, “Mean Shift Based Clustering in High Dimensions: A Texture Classification Example” Proc. Int'l Conf. Computer Vision, pp. 456–463, 2003.
13. A. Gionis, P. Indyk, and R. Motwani, “Similarity Search in High Dimensions via Hashing,” Proc. 25th Int'l Conf. Very Large Data Bases, pp. 518–529, 1999.
14. W. Grimson and D. Huttenlocher, “On the Sensitivity of Geometric Hashing,” Proc. Int'l Conf. Computer Vision, pp. 334-338,1990.
15. C.J. Harris and M. Stephens, “A Combined Corner and Edge Detector,” Proc. Fourth Alvey Vision Conf., pp. 147–151, 1988.
16. D. Huber, A. Kapuria, R. Donamukkala, and M. Hebert, “Part-Based 3D Object Classification,” Computer Vision and Pattern Recognition, vol. 2, pp. 82–89, June 2004.
17. P. Indyk and R. Motwani, “Approximate Nearest Neighbor—Towards Removing the Curse of Dimensionality,” Proc. 30th Symp. Theory of Computing, 1998.
18. A. Johnson and M. Hebert, “Surface Matching for Object Recognition in Complex Three-Dimensional Scenes,” Image and Vision Computing, vol. 16, pp. 635–651, 1998.
19. A. Johnson and M. Hebert, “Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, pp. 433–449, 1999.
20. A. Johnson, R. Hoffman, J. Osborn, and M. Hebert, “A System for Semi-Automatic Modeling of Complex Environments,” Proc. Int'l Conf. Recent Advances in 3-D Digital Imaging and Modeling, pp. 213–220 May 1997.
21. Y. Keselman, A. Shokoufandeh, M.F. Demirci, and S. Dickinson, “Many-to-Many Graph Matching via Metric Embedding,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2003.
22. Y. Lamdan and H. Wolfson, “Geometric Hashing: A General and Efficient Model-Based Recognition Scheme,” Proc. Int'l Conf. Computer Vision, pp. 238–249, 1988.
23. Y. Lamdan and H. Wolfson, “Affine Invariant Model-Based Object Recognition,” IEEE Trans. Robotics and Automation, vol. 6, no. 5, pp. 578–589, 1990.
24. D.G. Lowe, “Object Recognition from Local Scale-Invariant Features,” Proc. Int'l Conf. Computer Vision, pp. 525–531, 1999.
25. B. Matei and P. Meer, “A General Method for Errors-in-Variables Problems in Computer Vision,” Proc. Computer Vision and Pattern Recognition Conf., vol. 2, pp. 18–25, June 2000.
26. G. Medioni, M. Lee, and C. Tang, A Computational Framework for Feature Extraction and Segmentation. Elsevier Science, 2000.
27. G. Mori, S. Belongie, and J. Malik, “Shape Contexts Enable Efficient Retrieval of Similar Shapes,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 723–730, 2001.
28. S. Nene and S. Nayar, “A Simple Algorithm for Nearest-Neighbor Search in High Dimensions,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, pp. 989–1003, 1997.
29. D. Nister, “Preemptive RANSAC for Live Structure and Motion Estimation,” Proc. Int'l Conf. Computer Vision, pp. 199–206, 2003.
30. R. Osada, T. Funkhouser, B. Chazelle, and D. Dobkin, “Shape Distributions,” ACM Trans. Graphics, vol. 21, no. 4, pp. 807-832,2002.
31. I. Rigoutsos and R. Hummel, “A Bayesian Approach to Model Matching with Geometric Hashing,” Computer Vision and Image Understanding, vol. 61, no. 7, pp. 11–26 1995
32. S. Ruiz-Correa, L. Shapiro, and M. Melia, “A New Signature-Based Method for Efficient 3-D Object Recognition,” Computer Vision and Pattern Recognition, vol. 1, pp. 769–776, 2001.
33. S. Ruiz-Correa, L. Shapiro, and M. Miela, “A New Paradigm for Recognizing 3D Object Shapes from Range Data,” Proc. Int'l Conf. Computer Vision, pp. 1126–1133, 2003.
34. Y. Shan, H. Sawhney, S.S.B. Matei, and R. Kumar, “Partial Object Matching with Shapeme Histograms,” Proc. European Conf. Computer Vision, vol. 3, pp. 442–455, 2004.
35. Y. Shan, B. Matei, H.S. Sawhney, R. Kumar, D. Huber, and M. Hebert, “Linear Model Hashing and Batch RANSAC for Rapid and Accurate Object Recognition,” Computer Vision and Pattern Recognition, 2004.
36. G.C. Sharp, S.W. Lee, and D.K. Wehe, “ICP Registration Using Invariant Features,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 1, pp. 90–102, Jan. 2002.
37. F. Stein and G. Medioni, “Structural Indexing: Efficient Three-Dimensional Object Recognition,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 125–145, Feb. 1992.
38. P. Torr and A. Zisermann, “MLESAC: A New Robust Estimator with Application to Estimating Image Geometry,” Computer Vision and Image Understanding, vol. 78, pp. 138–156, 2000.
39. S. Yamany and A. Farag, “Surface Signatures: An Orientation Independent Free-Form Surface Representation Scheme for the Purpose of Object Registration and Matching,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 8, pp. 1105–1120, Aug. 2002.
40. D. Zhang and M. Hebert, “Harmonic Maps and Their Applications in Surface Matching,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, 1999.