F. Abdolali, R. A. Zoroofi, Y. Otake, and Y. Sato, Automatic segmentation of maxillofacial cysts in cone beam CT images, Computers in biology and medicine 72, pp.108-119, 2016.
DOI : 10.1016/j.compbiomed.2016.03.014

H. Akaike, An approximation to the density function, Annals of the Institute of Statistical Mathematics, vol.6, issue.2, pp.127-132, 1954.
DOI : 10.1007/BF02900741

I. Atadjanov and S. Lee, Bilateral symmetry detection based on scale invariant structure feature, 2015 IEEE International Conference on Image Processing (ICIP), pp.3447-3451, 2015.
DOI : 10.1109/ICIP.2015.7351444

I. R. Atadjanov and S. Lee, Reflection Symmetry Detection via Appearance of Structure Descriptor, European Conference on Computer Vision, pp.3-18, 2016.
DOI : 10.1109/CVPRW.2013.39

D. Cai, P. Li, F. Su, and Z. Zhao, An adaptive symmetry detection algorithm based on local features, 2014 IEEE Visual Communications and Image Processing Conference, pp.478-481, 2014.
DOI : 10.1109/VCIP.2014.7051610

J. Canny, A computational approach to edge detection, IEEE Transactions on pattern analysis and machine intelligence, issue.6, pp.679-698, 1986.

M. Cho and K. M. Lee, Bilateral Symmetry Detection via Symmetry-Growing, Procedings of the British Machine Vision Conference 2009, pp.1-11, 2009.
DOI : 10.5244/C.23.4

M. Cicconet, V. Birodkar, M. Lund, M. Werman, and D. Geiger, A convolutional approach to reflection symmetry, Pattern Recognition Letters, vol.95, 2017.
DOI : 10.1016/j.patrec.2017.03.022

URL : http://arxiv.org/abs/1609.05257

M. Cicconet, D. Geiger, K. C. Gunsalus, and M. Werman, Mirror Symmetry Histograms for Capturing Geometric Properties in Images, 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp.2981-2986, 2014.
DOI : 10.1109/CVPR.2014.381

URL : http://www.cs.huji.ac.il/%7Ewerman/Papers/2014_CVPR_MirrorSymmetry.pdf

D. Cremers, S. J. Osher, and S. Soatto, Kernel Density Estimation and Intrinsic Alignment for Shape Priors in Level Set Segmentation, International Journal of Computer Vision, vol.127, issue.2, pp.335-351, 2006.
DOI : 10.1007/s11263-006-7533-5

M. Elawady, C. Barat, C. Ducottet, and P. Colantoni, Global Bilateral Symmetry Detection Using Multiscale Mirror Histograms, International Conference on Advanced Concepts for Intelligent Vision Systems, pp.14-24, 2016.
DOI : 10.1145/2647868.2654930

URL : https://hal.archives-ouvertes.fr/ujm-01387193

A. Elgammal, R. Duraiswami, D. Harwood, and L. S. Davis, Background and foreground modeling using nonparametric kernel density estimation for visual surveillance, Proceedings of the IEEE, vol.90, issue.7, pp.1151-1163, 2002.
DOI : 10.1109/JPROC.2002.801448

URL : http://www.umiacs.umd.edu/~ramani/pubs/ieee_proc.pdf

M. Freeman, The Photographer's Eye: Composition and Design for Better Digital Photos, 2007.

E. García-portugués, R. M. Crujeiras, and W. González-manteiga, Kernel density estimation for directional???linear data, Journal of Multivariate Analysis, vol.121, pp.152-175, 2013.
DOI : 10.1016/j.jmva.2013.06.009

P. Hall, G. Watson, and J. Cabrera, Kernel density estimation with spherical data, Biometrika, vol.74, issue.4, pp.751-762, 1987.
DOI : 10.1093/biomet/74.4.751

J. A. Hobbs, R. Salome, and K. Vieth, The visual experience, 1995.

S. Kondra, A. Petrosino, and S. Iodice, Multi-scale Kernel Operators for Reflection and Rotation Symmetry: Further Achievements, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.217-222, 2013.
DOI : 10.1109/CVPRW.2013.39

J. Liu, G. Slota, G. Zheng, Z. Wu, M. Park et al., Symmetry Detection from RealWorld Images Competition 2013: Summary and Results, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.200-205, 2013.
DOI : 10.1109/CVPRW.2013.155

Y. Liu, H. Hel-or, and C. S. Kaplan, Computational Symmetry in Computer Vision and Computer Graphics, Foundations and Trends?? in Computer Graphics and Vision, vol.5, issue.1-2, 2010.
DOI : 10.1561/0600000008

URL : http://www.cse.psu.edu/~yanxi/0600000008-Liu.pdf

Z. Liu, R. Shi, L. Shen, Y. Xue, K. N. Ngan et al., Unsupervised Salient Object Segmentation Based on Kernel Density Estimation and Two-Phase Graph Cut, IEEE Transactions on Multimedia, vol.14, issue.4, pp.1275-1289, 2012.
DOI : 10.1109/TMM.2012.2190385

G. Loy and J. O. Eklundh, Detecting Symmetry and Symmetric Constellations of Features, Computer Vision?ECCV 2006, pp.508-521, 2006.
DOI : 10.1006/ciun.1993.1037

URL : http://www.nada.kth.se/~gareth/homepage/local_site/papers/loy_eccv2006.pdf

E. Michaelsen, D. Muench, and M. Arens, Recognition of Symmetry Structure by Use of Gestalt Algebra, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.206-210, 2013.
DOI : 10.1109/CVPRW.2013.37

Y. Ming, H. Li, and X. He, Symmetry detection via contour grouping, 2013 IEEE International Conference on Image Processing, pp.4259-4263, 2013.
DOI : 10.1109/ICIP.2013.6738877

A. Mittal and N. Paragios, Motion-based background subtraction using adaptive kernel density estimation, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., p.II?II. Ieee, 2004.
DOI : 10.1109/CVPR.2004.1315179

URL : http://www.umiacs.umd.edu/~anurag/cvpr2004.pdf

Q. Mo and B. Draper, Detecting bilateral symmetry with feature mirroring, CVPR 2011 Workshop on Symmetry Detection from Real World Images, 2011.

A. Pardo, E. Real, V. Krishnaswamy, J. M. López-higuera, B. W. Pogue et al., Directional Kernel Density Estimation for Classification of Breast Tissue Spectra, IEEE Transactions on Medical Imaging, vol.36, issue.1, pp.64-73, 2017.
DOI : 10.1109/TMI.2016.2593948

M. Park, S. Lee, P. C. Chen, S. Kashyap, A. A. Butt et al., Performance evaluation of state-of-the-art discrete symmetry detection algorithms, In: Computer Vision and Pattern Recognition IEEE, pp.1-8, 2008.

E. Parzen, On estimation of a probability density function and mode. The annals of mathematical statistics, pp.1065-1076, 1962.

V. Patraucean, R. G. Von-gioi, and M. Ovsjanikov, Detection of Mirror-Symmetric Image Patches, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.211-216, 2013.
DOI : 10.1109/CVPRW.2013.38

URL : http://www.lix.polytechnique.fr/%7Emaks/papers/CVPR2013w.pdf

S. Ram and J. J. Rodriguez, Vehicle detection in aerial images using multiscale structure enhancement and symmetry, 2016 IEEE International Conference on Image Processing (ICIP), pp.3817-3821, 2016.
DOI : 10.1109/ICIP.2016.7533074

I. Rauschert, K. Brocklehurst, S. Kashyap, J. Liu, and Y. Liu, First symmetry detection competition: Summary and results, Tech. rep, 2011.

H. R. Tavakoli, E. Rahtu, and J. Heikkilä, Fast and efficient saliency detection using sparse sampling and kernel density estimation, Scandinavian Conference on Image Analysis, pp.666-675, 2011.

J. Van-gemert, J. M. Geusebroek, C. Veenman, and A. Smeulders, Kernel Codebooks for Scene Categorization, Computer Vision?ECCV, vol.3, pp.696-709, 2008.
DOI : 10.1007/978-1-4899-3324-9

V. Vuollo, L. Holmström, H. Aarnivala, V. Harila, T. Heikkinen et al., Analyzing infant head flatness and asymmetry using kernel density estimation of directional surface data from a craniofacial 3D model, Statistics in Medicine, vol.21, issue.1, pp.4891-4904, 2016.
DOI : 10.1007/s10651-013-0249-0

M. Wang, X. S. Hua, T. Mei, R. Hong, G. Qi et al., Semi-supervised kernel density estimation for video annotation, Computer Vision and Image Understanding, vol.113, issue.3, pp.384-396, 2009.
DOI : 10.1016/j.cviu.2008.08.003

Z. Wang, Z. Tang, and X. Zhang, Reflection Symmetry Detection Using Locally Affine Invariant Edge Correspondence, IEEE Transactions on Image Processing, vol.24, issue.4, pp.1297-1301, 2015.
DOI : 10.1109/TIP.2015.2393060

Y. Yuan, Z. Xiong, and Q. Wang, An Incremental Framework for Video-Based Traffic Sign Detection, Tracking, and Recognition, IEEE Transactions on Intelligent Transportation Systems, vol.18, issue.7, 2016.
DOI : 10.1109/TITS.2016.2614548

R. D. Zakia and D. Page, Photographic Composition: A Visual Guide, 2010.

K. Zhang, M. Tang, and J. T. Kwok, Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.1001-1007, 2005.
DOI : 10.1109/CVPR.2005.73

S. Zhao, Y. Gao, X. Jiang, H. Yao, T. S. Chua et al., Exploring principlesof-art features for image emotion recognition, Proceedings of the ACM International Conference on Multimedia, pp.47-56, 2014.
DOI : 10.1145/2647868.2654930