Multi-scale Mesh Saliency with Local Patch Weighted Curvature Entropy

doi:10.16182/j.issn1004731x.joss.201709014

Journal of System Simulation ›› 2017, Vol. 29 ›› Issue (9): 1976-1983.doi: 10.16182/j.issn1004731x.joss.201709014

Previous Articles Next Articles

Multi-scale Mesh Saliency with Local Patch Weighted Curvature Entropy

Wang Xiaodong^1,2, Liang Hongtao^1,2, Kang Fengju^1,2, Gu Hao^1,2

1. Marine College, Northwestern Polytechnical University, Xi'an 710072, China;
2. National Key Laboratory of Underwater Information Process and Control, Xi'an 710072, China;

Received:2017-05-20 Online:2017-09-08 Published:2020-06-02
About author:Wang Xiaodong (1990-), Male, Yanan, China, Ph.D. research direction is research of system modeling and simulation.
Supported by:
Foundation items: Northwestern Polytechnical University doctoral dissertation Innovation Fund (CX201701)

Abstract

Abstract: Mesh saliency is an important geometrical characteristic of 3D mesh model and has been applied in many applications. Inspired by the existing algorithms, a novel multi-scale saliency detection method based on local patch weighted curvature entropy was proposed. A local coordinate system and curvature value of each vertex was estimated. An improved adaptive patch was defined on the tangent plane using accumulated volume of neighborhood. Furthermore, deviation of the patch of each vertex to their neighborhood was defined as the weight of curvature value. The Shannon entropy of weighted curvature values of neighbor vertices within a sphere centered at each vertex was defined as their saliency scores. Comparisons with state-of-the-art methods have shown the competitive performance in computation speed and the advantage in saliency detection ability of our method.

Key words: adaptive patch, mesh saliency, 3D mesh model, curvature

CLC Number:

TP391.9

Wang Xiaodong, Liang Hongtao, Kang Fengju, Gu Hao. Multi-scale Mesh Saliency with Local Patch Weighted Curvature Entropy[J]. Journal of System Simulation, 2017, 29(9): 1976-1983.

References

[1] Buschman T J, Miller E K.Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices[J]. Science (S0036-8075), 2007, 315(5820): 1860-1862.
[2] Zanto T P, Rubens M T, Thangavel A.Causal role of the prefrontal cortex in top-down modulation of visual processing and working memory[J]. Nature Neuroscience (S1097-6256), 2011, 14(5): 656-661.
[3] Lee C H, Kim Y, Varshney A.Saliency-Guided Lighting[J]. IEICE Transactions on Information & Systems (S1745-1361), 2009, 92(2): 369-373.
[4] Lee C H, Varshney A, Jacobs D W.Mesh saliency[J]. ACM Transactions on Graphics (S0730-0301), 2005, 24(3): 659-666.
[5] Leifman G, Shtrom E, Tal A.Surface regions of interest for viewpoint selection[C]// IEEE Conference on Computer Vision and Pattern Recognition. USA: IEEE, 2012: 414-421.
[6] Nouri A, Charrier C, Lézoray O.Multi-scale mesh saliency with local adaptive patches for viewpoint selection[J]. Signal Processing Image Communication (S0923-5965), 2015, 38: 151-166.
[7] Mao Z, Ma L, Zhao M.A Modified Laplacian Smoothing Approach with Mesh Saliency[M]. Berlin, Heidelberg, Germany: Springer, 2006: 105-113.
[8] Li Z, Ma L, Jin X.A new feature-preserving mesh-smoothing algorithm[J]. The Visual Computer (S1432-2315), 2009, 25(2): 139-148.
[9] Chen X, Saparov A, Pang B.Schelling Points on 3D Surface Meshes[J]. ACM Transactions on Graphics (S0730-0301), 2012, 31(4): 13-15.
[10] Wu J, Shen X, Zhu W.Mesh saliency with global rarity[J]. Graphical Models (S1524-0711), 2013, 75(5): 255-264.
[11] Song R, Liu Y, Martin R R.Mesh saliency via spectral processing[J]. ACM Transactions on Graphics (S0730-0301), 2014, 33(1): 57-76.
[12] Limper M, Kuijper A, Fellner D W.Mesh Saliency Analysis via Local Curvature Entropy[C]// Proceedings of the 37th Annual Conference of the European Association for Computer Graphics: Short Papers, France: Eurographics Association, 2016: 13-16.
[13] Tao P, Cao J, Li S.Mesh saliency via ranking unsalient patches in a descriptor space[J]. Computers & Graphics (S0097-8493), 2014, 46: 264-274.
[14] Liu X, Tao P, Cao J.Mesh saliency detection via double absorbing Markov chain in feature space[J]. The Visual Computer (S0272-1716), 2016, 32(9): 1121-1132.
[15] Nouri A, Charrier C, Lézoray O.Mesh saliency with adaptive local patches[C]// SPIE Electronic Imaging, Three-Dimensional Image Processing, Measurement (3DIPM), and Applications. USA: SPIE, 2015, 9393.
[16] Taubin G.Estimating the tensor of curvature of a surface from a polyhedral approximation[C]// International Conference on Computer Vision. USA: IEEE, 1995: 902-907.
[17] Gumhold S.Feature Extraction from Point Clouds[C]// 2001, Proc. 10th International Meshing Roundtable. USA: Sandia National Laboratories, 2001: 293-305.
[18] Neumann L, Sbert M, Gooch B.Viewpoint quality: Measures and applications[C]// Proceedings of the 1st Eurographics Workshop on Computational Aesthetics in Graphics, Visualization and Imaging. France: Eurographics Association, 2005: 185-192.
[19] Giorgi D, Biasotti S, Paraboschi L.Shape Retrieval Contest 2007: Watertight Models Track[J]. SHREC Competition, 2007, 8(7): 5-10.

Multi-scale Mesh Saliency with Local Patch Weighted Curvature Entropy

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 5

Recommended Articles

Metrics

Comments

[1]	Tian Ma, Yun Li, Jiaojiao Li, Yuancheng Li. Segmentation Line Detection in Dental Model Based on Target Region Constraint [J]. Journal of System Simulation, 2022, 34(2): 376-384.
[2]	Wu Jiaquan, Li Hongyan, Ye Fei, Zhang Xinyu, Ma Kun. Finite Element Numerical Simulation of Pre-damaged Reinforced Concrete Beam [J]. Journal of System Simulation, 2018, 30(9): 3437-3444.
[3]	Li Chunxi, Zhang Shuo, Ye Xuemin. Effect of Interfacial Curvature on Drag Reduction of Superhydrophobic Microchannels [J]. Journal of System Simulation, 2018, 30(6): 2405-2413.
[4]	Zhou Wen, Jia Jinyuan. Self-adaptive Simplification Algorithm for Suggestive-contours preserving [J]. Journal of System Simulation, 2016, 28(9): 2176-2185.
[5]	Yu Wenli, Zhou Mingquan, Shui Wuyang, Wu Zhongke. Automatic Registration Method Based on Curvature [J]. Journal of System Simulation, 2015, 27(10): 2374-2379.