Local binary patterns on triangular meshes: Concept and applications

A novel framework for computing local binary patterns on triangular mesh manifolds.Mesh-LBP evidences uniformity and repeatability aspects.Mesh-LBP descriptors can cope with mesh irregularities and global deformations.Mesh-LBP can be deployed in both local and global shape analysis.Experiments on 3D texture classification, retrieval and 3D face recognition. In this paper, we introduce an original framework for computing local binary like-patterns on 2D mesh manifolds (i.e., surfaces in the 3D space). This framework, dubbed mesh-LBP, preservers the simplicity and the adaptability of the 2D LBP and has the capacity of handling both open and close mesh surfaces without requiring normalization as compared to its 2D counterpart. We describe the foundations and the construction of mesh-LBP and showcase the different LBP patterns that can be generated on the mesh. In the experimentation, we provide evidence of the uniform patterns in the mesh-LBP, the repeatability of its descriptors, and its robustness to moderate shape deformations. Then, we show how the mesh-LBP descriptors can be adapted to a number of surface local and global analysis including 3D texture classification and retrieval, and 3D face matching. We also compare the performance of the mesh-LBP descriptors with a bunch of state of the art surface descriptors.

[1]  Ammad Ali,et al.  Face Recognition with Local Binary Patterns , 2012 .

[2]  Peijun Li,et al.  Rotation Invariant Texture Measured by Local Binary Pattern for Remote Sensing Image Classification , 2010, 2010 Second International Workshop on Education Technology and Computer Science.

[3]  Stefanos Zafeiriou,et al.  Local normal binary patterns for 3D facial action unit detection , 2012, 2012 19th IEEE International Conference on Image Processing.

[4]  Yaniv Taigman,et al.  Descriptor Based Methods in the Wild , 2008 .

[5]  Mohammed Bennamoun,et al.  Keypoint Detection and Local Feature Matching for Textured 3D Face Recognition , 2007, International Journal of Computer Vision.

[6]  Thomas A. Funkhouser,et al.  The Princeton Shape Benchmark , 2004, Proceedings Shape Modeling Applications, 2004..

[7]  R. Horaud,et al.  Surface feature detection and description with applications to mesh matching , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Iasonas Kokkinos,et al.  Intrinsic shape context descriptors for deformable shapes , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[9]  Leonidas J. Guibas,et al.  SHREC 2010: robust correspondence benchmark , 2010 .

[10]  Shengcai Liao,et al.  Face Detection Based on Multi-Block LBP Representation , 2007, ICB.

[11]  Robert B. Fisher,et al.  Finding Surface Correspondance for Object Recognition and Registration Using Pairwise Geometric Histograms , 1998, ECCV.

[12]  Alexander M. Bronstein,et al.  Numerical Geometry of Non-Rigid Shapes , 2009, Monographs in Computer Science.

[13]  Matti Pietikäinen,et al.  Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Matti Pietikäinen,et al.  Computer Vision Using Local Binary Patterns , 2011, Computational Imaging and Vision.

[15]  Jun Wang,et al.  A 3D facial expression database for facial behavior research , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[16]  M. Pietikäinen,et al.  SOFT HISTOGRAMS FOR LOCAL BINARY PATTERNS , 2007 .

[17]  Andrew E. Johnson,et al.  Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Bernard Chazelle,et al.  Shape distributions , 2002, TOGS.

[19]  Xiaoyang Tan,et al.  Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions , 2007, IEEE Transactions on Image Processing.

[20]  Shaogang Gong,et al.  Facial expression recognition based on Local Binary Patterns: A comprehensive study , 2009, Image Vis. Comput..

[21]  Stan Z. Li,et al.  Learning to Fuse 3D+2D Based Face Recognition at Both Feature and Decision Levels , 2005, AMFG.

[22]  Stefanos Zafeiriou,et al.  Binary Pattern Analysis for 3D Facial Action Unit Detection , 2012, BMVC.

[23]  Alberto Del Bimbo,et al.  Matching 3D face scans using interest points and local histogram descriptors , 2013, Comput. Graph..

[24]  Alberto Del Bimbo,et al.  The Mesh-LBP: A Framework for Extracting Local Binary Patterns From Discrete Manifolds , 2015, IEEE Transactions on Image Processing.

[25]  Matti Pietikäinen,et al.  Rotation-invariant texture classification using feature distributions , 2000, Pattern Recognit..

[26]  Majid Mirmehdi,et al.  Archive Film Restoration Based on Spatiotemporal Random Walks , 2010, ECCV.

[27]  Vijayalakshmi Atluri,et al.  Texture-Based Remote-Sensing Image Segmentation , 2005, 2005 IEEE International Conference on Multimedia and Expo.

[28]  Shu Liao,et al.  Face Recognition by Using Elongated Local Binary Patterns with Average Maximum Distance Gradient Magnitude , 2007, ACCV.

[29]  Yosi Keller,et al.  Scale-Invariant Features for 3-D Mesh Models , 2012, IEEE Transactions on Image Processing.

[30]  Hanqing Lu,et al.  Face detection using improved LBP under Bayesian framework , 2004, Third International Conference on Image and Graphics (ICIG'04).

[31]  Hans Burkhardt,et al.  3D rotation invariant local binary patterns , 2008, 2008 19th International Conference on Pattern Recognition.

[32]  Matti Pietikäinen,et al.  A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..

[33]  Liming Chen,et al.  3D facial expression recognition via multiple kernel learning of Multi-Scale Local Normal Patterns , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[34]  Matti Pietikäinen,et al.  Face Description with Local Binary Patterns: Application to Face Recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[35]  Xihong Wu,et al.  Boosting Local Binary Pattern (LBP)-Based Face Recognition , 2004, SINOBIOMETRICS.

[36]  Matti Pietikäinen,et al.  Optimising Colour and Texture Features for Real-time Visual Inspection , 2002, Pattern Analysis & Applications.

[37]  Di Huang,et al.  3-D Face Recognition Using eLBP-Based Facial Description and Local Feature Hybrid Matching , 2012, IEEE Transactions on Information Forensics and Security.

[38]  Alfred Stein,et al.  Multivariate texture‐based segmentation of remotely sensed imagery for extraction of objects and their uncertainty , 2005 .

[39]  Alberto Del Bimbo,et al.  The Mesh-LBP: Computing Local Binary Patterns on Discrete Manifolds , 2013, 2013 IEEE International Conference on Computer Vision Workshops.

[40]  Yiding Wang,et al.  A Robust Method for Near Infrared Face Recognition Based on Extended Local Binary Pattern , 2007, ISVC.

[41]  Tieniu Tan,et al.  Combining Statistics of Geometrical and Correlative Features for 3D Face Recognition , 2006, BMVC.

[42]  Yuming Zhao,et al.  Fast Tracking of Object Contour Based on Color and Texture , 2009, Int. J. Pattern Recognit. Artif. Intell..

[43]  Jiebo Luo,et al.  Heterogeneous feature machines for visual recognition , 2009, 2009 IEEE 12th International Conference on Computer Vision.