Weight-Optimal Local Binary Patterns

In this work, we have proposed a learning paradigm for obtaining weight-optimal local binary patterns (WoLBP). We first re-formulate the LBP problem into matrix multiplication with all the bitmaps flattened and then resort to the Fisher ratio criterion for obtaining the optimal weight matrix for LBP encoding. The solution is closed form and can be easily solved using one eigen-decomposition. The experimental results on the FRGC ver2.0 database have shown that the WoLBP gains significant performance improvement over traditional LBP, and such WoLBP learning procedure can be directly ported to many other LBP variants to further improve their performances.

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

[2]  Debin Zhao,et al.  Spatial Histogram Features for Face Detection in Color Images , 2004, PCM.

[3]  Matti Pietikäinen,et al.  Face Analysis Using Local Binary Patterns , 2008 .

[4]  Shengcai Liao,et al.  Learning Multi-scale Block Local Binary Patterns for Face Recognition , 2007, ICB.

[5]  Joel Z. Leibo,et al.  Subtasks of Unconstrained Face Recognition , 2014, 2014 International Conference on Computer Vision Theory and Applications (VISAPP).

[6]  Marios Savvides,et al.  Robust local binary pattern feature sets for periocular biometric identification , 2010, 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[7]  Stan Z. Li,et al.  Discriminant image filter learning for face recognition with local binary pattern like representation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Marios Savvides,et al.  Hallucinating the Full Face from the Periocular Region via Dimensionally Weighted K-SVD , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[9]  Changyin Sun,et al.  Gender Classification Based on Boosting Local Binary Pattern , 2006, ISNN.

[10]  Matti Pietikäinen,et al.  Learning Discriminant Face Descriptor , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Marios Savvides,et al.  An Augmented Linear Discriminant Analysis Approach for Identifying Identical Twins with the Aid of Facial Asymmetry Features , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[12]  Caifeng Shan,et al.  Learning local binary patterns for gender classification on real-world face images , 2012, Pattern Recognit. Lett..

[13]  Ching Y. Suen,et al.  Investigating age invariant face recognition based on periocular biometrics , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[14]  Shaogang Gong,et al.  Robust facial expression recognition using local binary patterns , 2005, IEEE International Conference on Image Processing 2005.

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

[16]  Marios Savvides,et al.  Can your eyebrows tell me who you are? , 2011, 2011 5th International Conference on Signal Processing and Communication Systems (ICSPCS).

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

[18]  Marwan Mattar,et al.  Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments , 2008 .

[19]  Domingo Mery,et al.  Learning discriminative local binary patterns for face recognition , 2011, Face and Gesture 2011.

[20]  Patrick J. Flynn,et al.  Overview of the face recognition grand challenge , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[21]  Marios Savvides,et al.  Subspace-Based Discrete Transform Encoded Local Binary Patterns Representations for Robust Periocular Matching on NIST’s Face Recognition Grand Challenge , 2014, IEEE Transactions on Image Processing.

[22]  Marios Savvides,et al.  Unconstrained periocular biometric acquisition and recognition using COTS PTZ camera for uncooperative and non-cooperative subjects , 2012, 2012 IEEE Workshop on the Applications of Computer Vision (WACV).

[23]  Marios Savvides,et al.  An image statistics approach towards efficient and robust refinement for landmarks on facial boundary , 2013, 2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS).

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

[25]  Tieniu Tan,et al.  Graph Matching Iris Image Blocks with Local Binary Pattern , 2006, ICB.

[26]  Marios Savvides,et al.  Facial Ethnic Appearance Synthesis , 2014, ECCV Workshops.