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View-Based Recognition Using an Eigenspace Approximation to the Hausdorff Measure
September 1999 (vol. 21 no. 9)
pp. 951-955

Abstract—View-based recognition methods, such as those using eigenspace techniques, have been successful for a number of recognition tasks. Such approaches, however, are somewhat limited in their ability to recognize objects that are partly hidden from view or occur against cluttered backgrounds. In order to address these limitations, we have developed a view matching technique based on an eigenspace approximation to the generalized Hausdorff measure. This method achieves the compact storage and fast indexing that are the main advantages of eigenspace view matching techniques, while also being tolerant of partial occlusion and background clutter. The method applies to binary feature maps, such as intensity edges, rather than directly to intensity images.

[1] D.P. Huttenlocher, G.A. Klanderman, and W.J. Rucklidge, “Comparing Images Using the Hausdorff Distance,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 9, pp. 850-863, Sept. 1993.
[2] K. Ohba and K. Ikeuchi, “Detectability, Uniqueness, and Reliability of Eigen-Windows for Stable Verification of Partially Occluded Objects,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 9, pp. 1,043-1,048, Sept. 1997.
[3] J. Krumm, “Eigenfeatures for Planar Pose Measurement of Partially Occluded Objects,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 55-66, 1996.
[4] H. Murase and S.K. Nayar, “Visual Learning and Recognition of 3-D Objects from Appearance,” Int'l J. Computer Vision, vol. 14, pp. 5-24, 1995.
[5] A. Pentland, B. Moghaddam, and Starner, "View-Based and Modular Eigenspaces for Face Recognition," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 1994, pp. 84-91.
[6] W.J. Rucklidge, “Locating Objects Using the Hausdorff Distance,” Proc. Int'l Conf. Computer Vision, pp. 457-464, 1995.
[7] M. Turk and A. Pentland, "Face Recognition Using Eigenfaces," Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 1991, pp. 586-591.
[8] S. Yoshimura and T. Kanade, “Fast Template Matching Based on the Normalized Correlation by Using Multiresolution Eigenimages,” Proc. Int'l Conf. Intelligent Robots and Systems, vol. 3, pp. 2,086-2,093, 1994.

Index Terms:
Model-based recognition, Hausdorff matching, subspace methods, image matching.
Citation:
Daniel P. Huttenlocher, Ryan H. Lilien, Clark F. Olson, "View-Based Recognition Using an Eigenspace Approximation to the Hausdorff Measure," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 9, pp. 951-955, Sept. 1999, doi:10.1109/34.790437
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