Global Bilateral Symmetry Detection Using Multiscale Mirror Histograms

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• 关键词：Symmetry detection ; Reflection symmetry ; Edge features ; Pairwise similarity ; Symmetry histogram
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：10016
• 期：1
• 页码：14-24
• 全文大小：3,107 KB
• 参考文献：1.Atadjanov, I., Lee, S.: Bilateral symmetry detection based on scale invariant structure feature. In: 2015 IEEE International Conference on Image Processing (ICIP), pp. 3447–3451. IEEE (2015)
  2.Bairagi, V.: Symmetry-based biomedical image compression. J. Digital Imaging 28, 718–726 (2015)CrossRef
  3.Cai, D., Li, P., Su, F., Zhao, Z.: An adaptive symmetry detection algorithm based on local features. In: 2014 IEEE Visual Communications and Image Processing Conference, pp. 478–481. IEEE (2014)
  4.Cho, M., Lee, K.M.: Bilateral symmetry detection via symmetry-growing. In: BMVC, pp. 1–11. Citeseer (2009)
  5.Cicconet, M., Geiger, D., Gunsalus, K.C., Werman, M.: Mirror symmetry histograms for capturing geometric properties in images. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2981–2986. IEEE (2014)
  6.Duda, R.O., Hart, P.E.: Use of the hough transformation to detect lines and curves in pictures. Commun. ACM 15(1), 11–15 (1972)CrossRef MATH
  7.Kondra, S., Petrosino, A., Iodice, S.: Multi-scale kernel operators for reflection and rotation symmetry: further achievements. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 217–222. IEEE (2013)
  8.Liu, J., Slota, G., Zheng, G., Wu, Z., Park, M., Lee, S., Rauschert, I., Liu, Y.: Symmetry detection from realworld images competition 2013: summary and results. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 200–205. IEEE (2013)
  9.Liu, Y., Hel-Or, H., Kaplan, C.S.: Computational Symmetry in Computer Vision and Computer Graphics. Now Publishers Inc., Boston (2010)MATH
  10.Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)CrossRef
  11.Loy, G., Eklundh, J.-O.: Detecting symmetry and symmetric constellations of features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 508–521. Springer, Heidelberg (2006). doi:10.​1007/​11744047_​39 CrossRef
  12.Michaelsen, E., Muench, D., Arens, M.: Recognition of symmetry structure by use of gestalt algebra. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 206–210. IEEE (2013)
  13.Ming, Y., Li, H., He, X.: Symmetry detection via contour grouping. In: 2013 20th IEEE International Conference on Image Processing (ICIP), pp. 4259–4263. IEEE (2013)
  14.Mo, Q., Draper, B.: Detecting bilateral symmetry with feature mirroring. In: CVPR 2011 Workshop on Symmetry Detection from Real World Images (2011)
  15.Murray, N., Marchesotti, L., Perronnin, F.: AVA: a large-scale database for aesthetic visual analysis. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2408–2415. IEEE (2012)
  16.Patraucean, V., von Gioi, R.G., Ovsjanikov, M.: Detection of mirror-symmetric image patches. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 211–216. IEEE (2013)
  17.Rauschert, I., Brocklehurst, K., Kashyap, S., Liu, J., Liu, Y.: First symmetry detection competition: summary and results. Technical report CSE11-012, Department of Computer Science and Engineering, The Pennsylvania State University (2011)
  18.Teo, C.L., Fermuller, C., Aloimonos, Y.: Detection and segmentation of 2D curved reflection symmetric structures. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1644–1652 (2015)
  19.Wang, Z., Tang, Z., Zhang, X.: Reflection symmetry detection using locally affine invariant edge correspondence. IEEE Trans. Image Process. 24(4), 1297–1301 (2015)MathSciNet CrossRef
  20.Yang, L., Liu, J., Tang, X.: Depth from water reflection. IEEE Trans. Image Process. 24(4), 1235–1243 (2015)MathSciNet CrossRef
  21.Zhao, S., Gao, Y., Jiang, X., Yao, H., Chua, T.S., Sun, X.: Exploring principles-of-art features for image emotion recognition. In: Proceedings of the ACM International Conference on Multimedia, pp. 47–56. ACM (2014)
  
• 作者单位：Mohamed Elawady (18)
  Cécile Barat (18)
  Christophe Ducottet (18)
  Philippe Colantoni (19)
  
  18. Universite Jean Monnet, CNRS, UMR 5516, Laboratoire Hubert Curien, 42000, Saint-Étienne, France
  19. Université Jean Monnet, Centre Interdisciplinaire d’Etudes et de Recherches sur l’Expression Contemporaine n° 3068, Saint-Étienne, France
  
• 丛书名：Advanced Concepts for Intelligent Vision Systems
• ISBN：978-3-319-48680-2
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：10016

文摘

In recent years, there has been renewed interest in bilateral symmetry detection in images. It consists in detecting the main bilateral symmetry axis inside artificial or natural images. State-of-the-art methods combine feature point detection, pairwise comparison and voting in Hough-like space. In spite of their good performance, they fail to give reliable results over challenging real-world and artistic images. In this paper, we propose a novel symmetry detection method using multi-scale edge features combined with local orientation histograms. An experimental evaluation is conducted on public datasets plus a new aesthetic-oriented dataset. The results show that our approach outperforms all other concurrent methods.