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Tactile mesh saliency

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Holly RushmeierAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 35, Issue 4

Article No.: 52, Pages 1 - 11

https://doi.org/10.1145/2897824.2925927

Published: 11 July 2016 Publication History

Abstract

While the concept of visual saliency has been previously explored in the areas of mesh and image processing, saliency detection also applies to other sensory stimuli. In this paper, we explore the problem of tactile mesh saliency, where we define salient points on a virtual mesh as those that a human is more likely to grasp, press, or touch if the mesh were a real-world object. We solve the problem of taking as input a 3D mesh and computing the relative tactile saliency of every mesh vertex. Since it is difficult to manually define a tactile saliency measure, we introduce a crowdsourcing and learning framework. It is typically easy for humans to provide relative rankings of saliency between vertices rather than absolute values. We thereby collect crowdsourced data of such relative rankings and take a learning-to-rank approach. We develop a new formulation to combine deep learning and learning-to-rank methods to compute a tactile saliency measure. We demonstrate our framework with a variety of 3D meshes and various applications including material suggestion for rendering and fabrication.

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References

[1]

Bächer, M., Bickel, B., James, D. L., and Pfister, H. 2012. Fabricating Articulated Characters from Skinned Meshes. ACM Trans. Graph. 31, 4 (July), 47:1--47:9.

Digital Library

[2]

Bohg, J., Morales, A., Asfour, T., and Kragic, D. 2014. Data-Driven Grasp Synthesis -- A Survey. IEEE Transactions on Robotics 30, 2, 289--309.

Digital Library

[3]

Borji, A., Sihite, D. N., and Itti, L. 2012. Salient Object Detection: A Benchmark. ECCV, 414--429.

[4]

Bylinskii, Z., Judd, T., Borji, A., Itti, L., Durand, F., Oliva, A., and Torralba, A., 2015. MIT Saliency Benchmark. http://saliency.mit.edu/.

[5]

Chapelle, O., and Keerthi, S. S. 2010. Efficient Algorithms for Ranking with SVMs. Information Retrieval 13, 3, 201--215.

Digital Library

[6]

Chen, D. Y., Tian, X.-P., Shen, Y.-T., and Ouhyoung, M. 2003. On Visual Similarity Based 3D Model Retrieval. Computer Graphics Forum 22, 3, 223--232.

[7]

Chen, X., Golovinskiy, A., and Funkhouser, T. 2009. A Benchmark for 3D Mesh Segmentation. ACM Trans. Graph. 28, 3 (July), 73:1--73:12.

Digital Library

[8]

Chen, X., Saparov, A., Pang, B., and Funkhouser, T. 2012. Schelling Points on 3D Surface Meshes. ACM Trans. Graph. 31, 4 (July), 29:1--29:12.

Digital Library

[9]

Cignoni, P., Pietroni, N., Malomo, L., and Scopigno, R. 2014. Field-aligned Mesh Joinery. ACM Trans. Graph. 33, 1 (Feb.), 11:1--11:12.

Digital Library

[10]

Dorsey, J., and Hanrahan, P. 1996. Modeling and Rendering of Metallic Patinas. In Proceedings of SIGGRAPH 96, Annual Conference Series, 387--396.

Digital Library

[11]

Gal, R., and Cohen-Or, D. 2006. Salient Geometric Features for Partial Shape Matching and Similarity. ACM Trans. Graph. 25, 1 (Jan.), 130--150.

Digital Library

[12]

Garces, E., Agarwala, A., Gutierrez, D., and Hertzmann, A. 2014. A Similarity Measure for Illustration Style. ACM Trans. Graph. 33, 4 (July), 93:1--93:9.

Digital Library

[13]

Gingold, Y., Shamir, A., and Cohen-Or, D. 2012. Micro Perceptual Human Computation for Visual Tasks. ACM Trans. Graph. 31, 5 (Sept.), 119:1--119:12.

Digital Library

[14]

Gingold, Y., Vouga, E., Grinspun, E., and Hirsh, H. 2012. Diamonds from the Rough: Improving Drawing, Painting, and Singing via Crowdsourcing. Proceedings of the AAAI Workshop on Human Computation (HCOMP).

[15]

Goferman, S., Zelnik-Manor, L., and Tal, A. 2012. Context-Aware Saliency Detection. PAMI 34, 10, 1915--1926.

Digital Library

[16]

Goldfeder, C., Ciocarlie, M., Dang, H., and Allen, P. K. 2009. The Columbia Grasp Database. ICRA, 3343--3349.

Digital Library

[17]

Hildebrand, K., Bickel, B., and Alexa, M. 2013. Orthogonal Slicing for Additive Manufacturing. SMI 37, 6, 669--675.

Digital Library

[18]

Hisada, M., Belyaev, A. G., and Kunii, T. L. 2002. A Skeleton-based Approach for Detection of Perceptually Salient Features on Polygonal Surfaces. CGF 21, 4, 689--700.

[19]

Horn, B. 1984. Extended Gaussian Images. Proceedings of the IEEE 72, 12, 1671--1686.

[20]

Howlett, S., Hamill, J., and O'Sullivan, C. 2005. Predicting and Evaluating Saliency for Simplified Polygonal Models. ACM Trans. on Applied Perception 2, 3 (July), 286--308.

Digital Library

[21]

Hu, J., Lu, J., and Tan, Y. P. 2014. Discriminative Deep Metric Learning for Face Verification in the Wild. CVPR, 1875--1882.

Digital Library

[22]

Hu, J., Lu, J., and Tan, Y. P. 2015. Deep Transfer Metric Learning. CVPR, 325--333.

[23]

Itti, L., Koch, C., and Niebur, E. 1998. A Model of Saliency-Based Visual Attention for Rapid Scene Analysis. PAMI 20, 11, 1254--1259.

Digital Library

[24]

Itti, L., 2000. Models of Bottom-Up and Top-Down Visual Attention. PhD Thesis, California Institute of Technology Pasadena.

Digital Library

[25]

Jain, A., Thormählen, T., Ritschel, T., and Seidel, H.-P. 2012. Material Memex: Automatic Material Suggestions for 3D Objects. ACM Trans. Graph. 31, 6 (Nov.), 143:1--143:8.

Digital Library

[26]

Järvelin, K., and Kekälänen, J. 2002. Cumulated Gain-based Evaluation of IR Techniques. ACM Trans. on Information Systems 20, 4, 422--446.

Digital Library

[27]

Kalogerakis, E., Hertzmann, A., and Singh, K. 2010. Learning 3D Mesh Segmentation and Labeling. ACM Trans. Graph. 29, 4 (July), 102:1--102:12.

Digital Library

[28]

Kim, Y., Varshney, A., Jacobs, D. W., and Guimbretière, F. 2010. Mesh Saliency and Human Eye Fixations. ACM Trans. on Applied Perception 7, 2 (Feb.), 12:1--12:13.

Digital Library

[29]

Klank, U., Pangercic, D., Rusu, R., and Beetz, M. 2009. Real-time CAD Model Matching for Mobile Manipulation and Grasping. IEEE-RAS Int'l Conf. on Humanoid Robots, 290--296.

[30]

Lau, M., Ohgawara, A., Mitani, J., and Igarashi, T. 2011. Converting 3D Furniture Models to Fabricatable Parts and Connectors. ACM Trans. Graph. 30, 4 (July), 85:1--85:6.

Digital Library

[31]

Lee, C. H., Varshney, A., and Jacobs, D. W. 2005. Mesh Saliency. ACM Trans. Graph. 24, 3 (July), 659--666.

Digital Library

[32]

Liu, Y., Zhu, H., Liu, X., and Wu, E. 2005. Real-time Simulation of Physically based On-Surface Flow. The Visual Computer 21, 8-10, 727--734.

[33]

Liu, T., Hertzmann, A., Li, W., and Funkhouser, T. 2015. Style Compatibility for 3D Furniture Models. ACM Trans. Graph. 34, 4 (July), 85:1--85:9.

Digital Library

[34]

Liu, Z., Wang, X., and Bu, S. 2015. Human-Centered Saliency Detection. IEEE Trans. on Neural Networks and Learning Systems.

[35]

Mérillou, S., and Ghazanfarpour, D. 2008. A Survey of Aging and Weathering Phenomena in Computer Graphics. Computers & Graphics 32, 2, 159--174.

Digital Library

[36]

O'Donovan, P., Libeks, J., Agarwala, A., and Hertzmann, A. 2014. Exploratory Font Selection Using Crowd-sourced Attributes. ACM Trans. Graph. 33, 4 (July), 92:1--92:9.

Digital Library

[37]

Osada, R., Funkhouser, T., Chazelle, B., and Dobkin, D. 2001. Matching 3D Models with Shape Distributions. Shape Modeling International, 154--166.

Digital Library

[38]

Parikh, D., and Grauman, K. 2011. Relative Attributes. International Conference on Computer Vision (ICCV), 503--510.

Digital Library

[39]

Plaisier, M. A., Tiest, W. M. B., and Kappers, A. M. L. 2009. Salient Features in 3-D Haptic Shape Perception. Attention, Perception, & Psychophysics 71, 2, 421--430.

[40]

Prévost, R., Whiting, E., Lefebvre, S., and Sorkine-Hornung, O. 2013. Make It Stand: Balancing Shapes for 3D Fabrication. ACM Trans. Graph. 32, 4 (July), 81:1--81:10.

Digital Library

[41]

Sahbani, A., and El-Khoury, S. 2009. A Hybrid Approach for Grasping 3D Objects. IROS, 1272--1277.

Digital Library

[42]

Sahbani, A., El-khoury, S., and Bidaud, P. 2012. An Overview of 3D Object Grasp Synthesis Algorithms. Robotics and Autonomous Systems 60, 3, 326--336.

Digital Library

[43]

Saxena, A., Driemeyer, J., Kearns, J., and Ng, A. Y. 2007. Robotic Grasping of Novel Objects. NIPS, 1209--1216.

[44]

Schwartzburg, Y., and Pauly, M. 2013. Fabrication-aware Design with Intersecting Planar Pieces. CGF 32, 2, 317--326.

[45]

Shilane, P., and Funkhouser, T. 2007. Distinctive Regions of 3D Surfaces. ACM Trans. Graph. 26, 2 (June), 7.

Digital Library

[46]

Shilane, P., Min, P., Kazhdan, M., and Funkhouser, T. 2004. The Princeton Shape Benchmark. SMI, 167--178.

Digital Library

[47]

Shtrom, E., Leifman, G., and Tal, A. 2013. Saliency Detection in Large Point Sets. ICCV, 3591--3598.

Digital Library

[48]

Song, R., Liu, Y., Martin, R. R., and Rosin, P. L. 2014. Mesh Saliency via Spectral Processing. ACM Trans. Graph. 33, 1 (Feb.), 6:1--6:17.

Digital Library

[49]

Su, H., Maji, S., Kalogerakis, E., and Learned-Miller, E. 2015. Multi-view Convolutional Neural Networks for 3D Shape Recognition. ICCV.

Digital Library

[50]

Surazhsky, T., Magid, E., Soldea, O., Elber, G., and Rivlin, E. 2003. A Comparison of Gaussian and Mean Curvatures Estimation Methods on Triangular Meshes. International Conference on Robotics and Automation, 1021--1026.

[51]

Tao, P., Cao, J., Li, S., Liu, X., and Liu, L. 2015. Mesh Saliency via Ranking Unsalient Patches in a Descriptor Space. Computers and Graphics 46, C, 264--274.

Digital Library

[52]

Varadarajan, K., Potapova, E., and Vincze, M. 2012. Attention driven Grasping for Clearing a Heap of Objects. IROS, 2035--2042.

[53]

Wang, J., Song, Y., Leung, T., Rosenberg, C., Wang, J., Philbin, J., Chen, B., and Wu, Y. 2014. Learning Fine-Grained Image Similarity with Deep Ranking. CVPR, 1386--1393.

Digital Library

[54]

Watanabe, K., and Belyaev, A. G. 2001. Detection of Salient Curvature Features on Polygonal Surfaces. CGF 20, 3, 385--392.

[55]

Wei, L., Huang, Q., Ceylan, D., Vouga, E., and Li, H. 2015. Dense Human Body Correspondences Using Convolutional Networks. CVPR.

[56]

Xu, M., Ni, B., Dong, J., Huang, Z., Wang, M., and Yan, S. 2012. Touch Saliency. ACM International Conference on Multimedia, 1041--1044.

Digital Library

[57]

Zagoruyko, S., and Komodakis, N. 2015. Learning to Compare Image Patches via Convolutional Neural Networks. CVPR.

[58]

Zhou, Q., Panetta, J., and Zorin, D. 2013. Worst-case Structural Analysis. ACM Trans. Graph. 32, 4 (July), 137:1--137:12.

Digital Library

[59]

Zimmer, H., Lafarge, F., Alliez, P., and Kobbelt, L. 2014. Zometool Shape Approximation. Graphical Models 76, 5, 390--401.

Digital Library

Cited By

Chen MLau M(2024)Enhancing the Aesthetics of 3D Shapes via Reference-based EditingACM Transactions on Graphics10.1145/368795443:6(1-15)Online publication date: 19-Dec-2024
https://dl.acm.org/doi/10.1145/3687954
Ujitoko YBan YYokosaka T(2024)Elucidating Diurnal Patterns in Touch Desire Using Social Media Data Toward Design of Haptic Applications and DisplaysIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.335541330:12(7592-7600)Online publication date: Dec-2024
https://doi.org/10.1109/TVCG.2024.3355413
Wang SLiu XWang CLiu J(2024)Physics-aware iterative learning and prediction of saliency map for bimanual grasp planningComputer Aided Geometric Design10.1016/j.cagd.2024.102298111(102298)Online publication date: Jun-2024
https://doi.org/10.1016/j.cagd.2024.102298
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Index Terms

Tactile mesh saliency
1. Computing methodologies
  1. Computer graphics
    1. Shape modeling

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 35, Issue 4

July 2016

1396 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/2897824

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Copyright © 2016 ACM.

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Publication History

Published: 11 July 2016

Published in TOG Volume 35, Issue 4

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Cited By

Chen MLau M(2024)Enhancing the Aesthetics of 3D Shapes via Reference-based EditingACM Transactions on Graphics10.1145/368795443:6(1-15)Online publication date: 19-Dec-2024
https://dl.acm.org/doi/10.1145/3687954
Ujitoko YBan YYokosaka T(2024)Elucidating Diurnal Patterns in Touch Desire Using Social Media Data Toward Design of Haptic Applications and DisplaysIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.335541330:12(7592-7600)Online publication date: Dec-2024
https://doi.org/10.1109/TVCG.2024.3355413
Wang SLiu XWang CLiu J(2024)Physics-aware iterative learning and prediction of saliency map for bimanual grasp planningComputer Aided Geometric Design10.1016/j.cagd.2024.102298111(102298)Online publication date: Jun-2024
https://doi.org/10.1016/j.cagd.2024.102298
Luo HZhai WZhang JCao YTao D(2024)Grounded Affordance from Exocentric ViewInternational Journal of Computer Vision10.1007/s11263-023-01962-z132:6(1945-1969)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s11263-023-01962-z
Martin DFandos AMasia BSerrano A(2024)SAL3D: a model for saliency prediction in 3D meshesThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-023-03206-040:11(7761-7771)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1007/s00371-023-03206-0
Shu ZGao LYi SWu FDing XWan TXin S(2023)Context-Aware 3D Points of Interest Detection via Spatial Attention MechanismACM Transactions on Multimedia Computing, Communications, and Applications10.1145/359702619:6(1-19)Online publication date: 12-Jul-2023
https://dl.acm.org/doi/10.1145/3597026
Chen MLau M(2023)Learning 3D Shape Aesthetics Globally and LocallyComputer Graphics Forum10.1111/cgf.1470241:7(579-588)Online publication date: 20-Mar-2023
https://doi.org/10.1111/cgf.14702
Chen GDai HZhou TShen JShao L(2023)Automatic Schelling Point Detection From MeshesIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.314414329:6(2926-2939)Online publication date: 1-Jun-2023
https://doi.org/10.1109/TVCG.2022.3144143
Song RZhang WZhao YLiu YRosin P(2023)3D Visual Saliency: An Independent Perceptual Measure or A Derivative of 2D Image Saliency?IEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2023.3287356(1-17)Online publication date: 2023
https://doi.org/10.1109/TPAMI.2023.3287356
Ujitoko YBan Y(2023)Toward Designing Haptic Displays for Desired Touch Targets: A Study of User Expectation for Haptic Properties via CrowdsourcingIEEE Transactions on Haptics10.1109/TOH.2023.331066216:4(726-735)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1109/TOH.2023.3310662
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