Abstract
The paper investigates a certain group of problems in visual detection and identification of near-identical the-same-class objects. We focus on difficult problems for which: (1) the intra-class visual differences are comparable to inter-class differences, (2) views of the objects are distorted both photometrically and geometrically, and (3) objects are randomly placed in images of unpredictable contents. Since detection of the-same-person faces in complex images is one of such problems, we use it as the case study for the proposed approach. The approach combines a relatively inexpensive technique of near-duplicate fragment detection with a novel co-segmentation algorithm. Thus, the initial pool of matching candidates can be found quickly (however, with limited precision, i.e. many false positives can be detected). It is shown that the subsequent co-segmentation can effectively reject false positives and accurately extract the matching objects from random backgrounds.
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References
Philbin, J., Chum, O., Isard, M., Sivic, J., Zisserman, A.: Object Retrieval with Large Vocabularies and Fast Spatial Matching. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2007), pp. 1–8 (2007)
Zhao, W.-L., Ngo, C.-W.: Scale-rotation Invariant Pattern Entropy for Keypoint-based Near-duplicate Detection. IEEE Trans. Image Process. 2, 412–423 (2009)
Paradowski, M., Śluzek, A.: Local Keypoints and Global Affine Geometry: Triangles and Ellipses for Image Fragment Matching. In: Kwaśnicka, H., Jain, L.C. (eds.) Innovations in Intelligent Image Analysis. SCI, vol. 339, pp. 195–224. Springer, Heidelberg (2011)
Chum, O., Perdoch, M., Matas, J.: Geometric min-Hashing: Finding a (Thick) Needle in a Haystack. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2009), pp. 17–24 (2009)
Śluzek, A., Paradowski, M.: Visual Similarity Issues in Face Recognition. Int. J. Biometrics 4, 22–37 (2012)
Tell, D., Carlsson, S.: Combining Appearance and Topology for Wide Baseline Matching. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part I. LNCS, vol. 2350, pp. 68–81. Springer, Heidelberg (2002)
Li, H., Kim, E., Huang, X., He, L.: Object Matching with a Locally Affine-Invariant Constraint. In: IEEE Confernce on Computer Vision and Pattern Recognition (CVPR 2010), pp. 1641–1648 (2010)
Cech, J., Matas, J., Perdoch, M.: Efficient Sequential Correspondence Selection by Cosegmentation. IEEE Trans. PAMI 32, 1568–1581 (2010)
Vicente, S., Rother, C., Kolmogorov, V.: Object Cosegmentation. In: IEEE Confernce on Computer Vision and Pattern Recognition (CVPR 2011), pp. 2217–2224 (2011)
Yang, D., Śluzek, A.: Co-segmentation by Keypoint Matching: Incorporating Pixel-to-pixel Mapping into MRF. Nanyang Technological University, SCE - unpublished report, Singapore (2010)
Hochbaum, D.S., Singh, V.: An Efficient Algorithm for Co-segmentation. In: 12th IEEE International Conference on Computer Vision (ICCV 2009), pp. 269–276 (2009)
Mukherjee, L., Singh, V., Dyer, C.R.: Half-integrality based algorithms for cosegmentation of images. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2009), pp. 2028–2035 (2009)
Yang, D., Śluzek, A.: A Low-dimensional Local Descriptor Incorporating TPS Warping for Image Matching. Image Vision Comput. 28, 1184–1195 (2010)
Bookstein, F.L.: Principle Warps: Thin Plate Splines and the Decomposition of Deformations. IEEE Trans. PAMI 16, 460–468 (1989)
Mikolajczyk, K., Schmid, C.: Scale and Affine Invariant Interest Point Detectors. Int. J. Comput. Vision 60, 63–86 (2004)
Lowe, D.G.: Distinctive Image Features from Scale-invariant Keypoints. Int. J. Comput. Vision 60, 91–110 (2004)
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Śluzek, A., Paradowski, M., Yang, D. (2012). Reinforcement of Keypoint Matching by Co-segmentation in Object Retrieval: Face Recognition Case Study. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34500-5_5
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DOI: https://doi.org/10.1007/978-3-642-34500-5_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34499-2
Online ISBN: 978-3-642-34500-5
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