G. H. Bower and A. L. Glass, Structural units and the redintegrative power of picture fragments., Journal of Experimental Psychology: Human Learning and Memory, vol.2, issue.4, p.456, 1976.
DOI : 10.1037/0278-7393.2.4.456

D. D. Hoffman and M. Singh, Salience of visual parts, Cognition, vol.63, issue.1, pp.29-78, 1997.
DOI : 10.1016/S0010-0277(96)00791-3

V. Léon, N. Bonneel, G. Lavoué, and J. Vandeborre, Continuous semantic description of 3D meshes, Computers & Graphics, vol.54, pp.47-56, 2016.
DOI : 10.1016/j.cag.2015.07.018

E. Guy, J. Thiery, and T. Boubekeur, SimSelect: Similarity-based selection for 3D surfaces, Computer Graphics Forum, vol.29, issue.2, pp.165-173, 2014.
DOI : 10.1145/2366145.2366195
URL : https://hal.archives-ouvertes.fr/hal-01117089

L. J. Larsson, G. Morin, A. Begault, R. Chaine, J. Abiva et al., Identifying Perceptually Salient Features on 2D Shapes, Research in Shape Modeling, pp.129-153, 2015.
DOI : 10.1007/978-3-319-16348-2_9
URL : https://hal.archives-ouvertes.fr/hal-01071631

K. Leonard, G. Morin, S. Hahmann, and A. Carlier, A 2D shape structure for decomposition and part similarity, 2016 23rd International Conference on Pattern Recognition (ICPR), pp.2016-3216, 2016.
DOI : 10.1109/ICPR.2016.7900130
URL : https://hal.archives-ouvertes.fr/hal-01374810

A. Borji and L. Itti, State-of-the-Art in Visual Attention Modeling, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.1, pp.185-207, 2013.
DOI : 10.1109/TPAMI.2012.89

L. Itti, C. Koch, and E. Niebur, A model of saliency-based visual attention for rapid scene analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.11, pp.1254-1259, 1998.
DOI : 10.1109/34.730558
URL : http://www.klab.caltech.edu/~itti/attention/publications/98_PAMI/paper.ps.gz

C. H. Lee, A. Varshney, D. W. Jacobs, and M. Saliency, Mesh saliency, ACM Transactions on Graphics, vol.24, issue.3, pp.659-666, 2005.
DOI : 10.1145/1073204.1073244

R. Song, Y. Liu, R. R. Martin, and P. L. Rosin, Mesh saliency via spectral processing, ACM Transactions on Graphics, vol.33, issue.1, 2014.
DOI : 10.1016/j.imavis.2008.07.009
URL : http://ralph.cs.cf.ac.uk/papers/Geometry/MeshSaliency.pdf

R. Song, Y. Liu, R. R. Martin, and K. R. Echavarria, Local-to-global mesh saliency, The Visual Computer, vol.20, issue.1, pp.1-14, 2016.
DOI : 10.1007/s00371-016-1334-9
URL : http://eprints.brighton.ac.uk/16994/1/template.pdf

A. Nouri, C. Charrier, and O. Lézoray, Multi-scale mesh saliency with local adaptive patches for viewpoint selection, Signal Processing, Image Communication, vol.38, pp.151-166, 2015.
DOI : 10.1016/j.image.2015.08.002
URL : https://hal.archives-ouvertes.fr/hal-01252849/document

D. H. Kim, I. D. Yun, and S. U. Lee, A new shape decomposition scheme for graph-based representation, Pattern Recognition, vol.38, issue.5, pp.673-689, 2005.
DOI : 10.1016/j.patcog.2004.10.003

X. Chen, A. Saparov, B. Pang, and T. Funkhouser, Schelling points on 3D surface meshes, ACM Transactions on Graphics, vol.31, issue.4, 2012.
DOI : 10.1145/2185520.2185525
URL : http://www.cs.princeton.edu/%7Efunk/schelling.pdf

P. Theologou, I. Pratikakis, and T. Theoharis, A comprehensive overview of methodologies and performance evaluation frameworks in 3D mesh segmentation, Computer Vision and Image Understanding, vol.135, pp.49-82, 2015.
DOI : 10.1016/j.cviu.2014.12.008

Z. Xie, K. Xu, L. Liu, and Y. , 3D Shape Segmentation and Labeling via Extreme Learning Machine, Computer Graphics Forum, vol.29, issue.6, pp.85-95, 2014.
DOI : 10.1111/j.1467-8659.2011.01893.x
URL : http://www.kevinkaixu.net/k/papers/xie_sgp14_elmseg.pdf

H. Benhabiles, G. Lavoué, J. Vandeborre, and M. Daoudi, Learning Boundary Edges for 3D-Mesh Segmentation, Computer Graphics Forum, vol.26, issue.5, pp.2170-2182, 2011.
DOI : 10.1016/S0097-8493(02)00128-0
URL : https://hal.archives-ouvertes.fr/hal-00660740

Y. Lai, S. Hu, R. R. Martin, and P. L. Rosin, Rapid and effective segmentation of 3D models using random walks, Computer Aided Geometric Design, vol.26, issue.6, pp.665-679, 2009.
DOI : 10.1016/j.cagd.2008.09.007
URL : http://users.cs.cf.ac.uk/Paul.Rosin/resources/papers/segmentation-CAGD-postprint.pdf

F. Bergamasco, A. Albarelli, and A. Torsello, A graph-based technique for semi-supervised segmentation of 3D surfaces, Pattern Recognition Letters, vol.33, issue.15, pp.2057-2064, 2012.
DOI : 10.1016/j.patrec.2012.03.015
URL : https://iris.unive.it/bitstream/10278/34353/1/published.pdf

Y. Fang, M. Sun, M. Kim, and K. Ramani, Heat-mapping: A robust approach toward perceptually consistent mesh segmentation, CVPR 2011, pp.2145-2152, 2011.
DOI : 10.1109/CVPR.2011.5995695
URL : https://engineering.purdue.edu/PRECISE/Publications/heatmapping-a-robust-approach-toward-perceptually-consistent-mesh-segmentation/1747.pdf

O. K. Au, Y. Zheng, M. Chen, P. Xu, and C. Tai, Mesh segmentation with concavity-aware fields, IEEE Transactions on Visualization and Computer Graphics, vol.18, issue.7, pp.1125-1134, 2012.

S. Pulla, A. Razdan, and G. Farin, Improved curvature estimation for watershed segmentation of 3-dimensional meshes, IEEE Trans. on Visualization and Computer Graphics, vol.5, issue.4, pp.308-321, 2001.

A. Koschan, Perception-based 3D triangle mesh segmentation using fast marching watersheds, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., p.27, 2003.
DOI : 10.1109/CVPR.2003.1211448
URL : http://imaging.utk.edu/publications/papers/2003/page_cvpr03.pdf

S. Berretti, A. Del-bimbo, and P. , 3D Mesh decomposition using Reeb graphs, Image and Vision Computing, vol.27, issue.10, pp.1540-1554, 2009.
DOI : 10.1016/j.imavis.2009.02.004
URL : http://www.dsi.unifi.it/~berretti/download/ivc09.pdf

S. Biasotti, D. Giorgi, M. Spagnuolo, and B. Falcidieno, Reeb graphs for shape analysis and applications, Theoretical Computer Science, vol.392, issue.1-3, pp.5-22, 2008.
DOI : 10.1016/j.tcs.2007.10.018
URL : https://doi.org/10.1016/j.tcs.2007.10.018

T. El-gaaly, V. Froyen, A. Elgammal, J. Feldman, and M. Singh, A bayesian approach to perceptual 3d object-part decomposition using skeleton-based representations, Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, pp.3762-3768, 2015.

X. Li, T. W. Woon, T. S. Tan, and Z. Huang, Decomposing polygon meshes for interactive applications, Proceedings of the 2001 symposium on Interactive 3D graphics , SI3D '01, pp.35-42, 2001.
DOI : 10.1145/364338.364343

J. Kustra, A. Jalba, and A. Telea, Shape segmentation using medial point clouds with applications to dental cast analysis, Proc. of the 9th Int. Conf. on Computer Vision Theory and Applications, pp.2014-162, 2014.

C. Feng, A. C. Jalba, and A. C. Telea, Part-Based Segmentation by Skeleton Cut Space Analysis, Int. Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing, pp.607-618, 2015.
DOI : 10.1007/978-3-319-18720-4_51

J. Tierny, J. Vandeborre, and M. Daoudi, Topology driven 3D mesh hierarchical segmentation, IEEE International Conference on Shape Modeling and Applications 2007 (SMI '07), pp.215-220, 2007.
DOI : 10.1109/SMI.2007.38
URL : https://hal.archives-ouvertes.fr/hal-00725321

L. Liu, E. W. Chambers, D. Letscher, and T. Ju, Extended grassfire transform on medial axes of 2D shapes, Computer-Aided Design, vol.43, issue.11, pp.1496-1505, 2011.
DOI : 10.1016/j.cad.2011.09.002

Y. Yan, K. Sykes, E. Chambers, D. Letscher, and T. Ju, Erosion thickness on medial axes of 3D shapes, ACM Transactions on Graphics, vol.35, issue.4, pp.1-3812, 2016.
DOI : 10.1145/1060244.1060250

A. Carlier, K. Leonard, S. Hahmann, G. Morin, and M. Collins, The 2D shape structure dataset: A user annotated open access database, Computers & Graphics, vol.58, pp.23-30, 2016.
DOI : 10.1016/j.cag.2016.05.009
URL : https://hal.archives-ouvertes.fr/hal-01322964

T. K. Dey and J. Sun, Defining and computing curve-skeletons with medial geodesic function, in: Symposium on geometry processing, pp.143-152, 2006.

J. Giesen, B. Miklos, M. Pauly, and C. Wormser, The scale axis transform, Proceedings of the 25th annual symposium on Computational geometry, SCG '09, pp.106-115, 2009.
DOI : 10.1145/1542362.1542388

N. Amenta, M. Bern, and M. Kamvysselis, A new Voronoi-based surface reconstruction algorithm, Proceedings of the 25th annual conference on Computer graphics and interactive techniques , SIGGRAPH '98, pp.415-421, 1998.
DOI : 10.1145/280814.280947

A. Tagliasacchi, T. Delame, M. Spagnuolo, N. Amenta, and A. Telea, 3D Skeletons: A State-of-the-Art Report, Computer Graphics Forum, vol.29, issue.2, pp.573-597, 2016.
DOI : 10.1109/TMI.2006.884634
URL : https://hal.archives-ouvertes.fr/hal-01300281

A. Tagliasacchi, I. Alhashim, M. Olson, and H. Zhang, Mean Curvature Skeletons, Computer Graphics Forum, vol.29, issue.2, pp.1735-1744, 2012.
DOI : 10.1111/j.1467-8659.2009.01633.x

T. Lee, R. L. Kashyap, and C. Chu, Building Skeleton Models via 3-D Medial Surface Axis Thinning Algorithms, CVGIP: Graphical Models and Image Processing, vol.56, issue.6, pp.462-478, 1994.
DOI : 10.1006/cgip.1994.1042

M. Livesu, F. Guggeri, and R. Scateni, Reconstructing the Curve-Skeletons of 3D Shapes Using the Visual Hull, IEEE Transactions on Visualization and Computer Graphics, vol.18, issue.11, pp.1891-1901, 2012.
DOI : 10.1109/TVCG.2012.71

M. Livesu and R. Scateni, Extracting curve-skeletons from digital shapes using occluding contours, The Visual Computer, vol.14, issue.4, pp.907-916, 2013.
DOI : 10.1109/TVCG.2008.38

R. Tibshirani, G. Walther, and T. Hastie, Estimating the number of clusters in a data set via the gap statistic, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.63, issue.2, pp.411-423, 2001.
DOI : 10.1111/1467-9868.00293

G. Leifman and A. , Pattern-Driven Colorization of 3D Surfaces, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.241-248, 2013.
DOI : 10.1109/CVPR.2013.38