Deep feature representation and ball-tree for face sketch recognition

Forensic face sketch-photo recognition attracts considerable interest in the law enforcement agencies. This paper proposes a new face sketch-photo recognition method based on the VGG deep feature and ball-tree searching algorithm. In this paper, the recognition performances by different feature layers of pretrained VGG-Face model are explored. In addition, to accelerate the matching speed, the ball-tree algorithm is adopted to search the nearest neighbors of query sketches from gallery photos. The experimental results on CUFS and IIIT-D datasets demonstrate the superiority of the proposed method compared with existing algorithms.

[1]  Richa Singh,et al.  Composite sketch recognition via deep network - a transfer learning approach , 2015, 2015 International Conference on Biometrics (ICB).

[2]  Vijayan K. Asari,et al.  Local Difference of Gaussian Binary Pattern: Robust Features for Face Sketch Recognition , 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

[3]  Reuben A. Farrugia,et al.  Face photo-sketch recognition using local and global texture descriptors , 2016, 2016 24th European Signal Processing Conference (EUSIPCO).

[4]  Andrew Zisserman,et al.  Deep Face Recognition , 2015, BMVC.

[5]  Davis E. King,et al.  Dlib-ml: A Machine Learning Toolkit , 2009, J. Mach. Learn. Res..

[6]  Andrea Vedaldi,et al.  MatConvNet: Convolutional Neural Networks for MATLAB , 2014, ACM Multimedia.

[7]  Frédéric Jurie,et al.  CMML: a New Metric Learning Approach for Cross Modal Matching , 2012, ACCV 2012.

[8]  Xinbo Gao,et al.  Recognition of facial sketch styles , 2015, Neurocomputing.

[9]  Xinbo Gao,et al.  Graphical Representation for Heterogeneous Face Recognition , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Andrew W. Moore,et al.  New Algorithms for Efficient High-Dimensional Nonparametric Classification , 2006, J. Mach. Learn. Res..

[11]  Hamed Kiani Galoogahi,et al.  Inter-modality Face Sketch Recognition , 2012, 2012 IEEE International Conference on Multimedia and Expo.

[12]  Reuben A. Farrugia,et al.  Forensic Face Photo-Sketch Recognition Using a Deep Learning-Based Architecture , 2017, IEEE Signal Processing Letters.

[13]  Chunna Tian,et al.  Face Sketch Synthesis Algorithm Based on E-HMM and Selective Ensemble , 2008, IEEE Transactions on Circuits and Systems for Video Technology.

[14]  Xiaogang Wang,et al.  Coupled information-theoretic encoding for face photo-sketch recognition , 2011, CVPR 2011.

[15]  Shiguang Shan,et al.  Multi-view Discriminant Analysis , 2012, ECCV.

[16]  Himanshu S. Bhatt,et al.  Memetic approach for matching sketches with digital face images , 2012 .

[17]  Nasser M. Nasrabadi,et al.  Attribute-Centered Loss for Soft-Biometrics Guided Face Sketch-Photo Recognition , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[18]  Hao Zhou,et al.  Markov Weight Fields for face sketch synthesis , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[19]  James Philbin,et al.  FaceNet: A unified embedding for face recognition and clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[20]  Anil K. Jain,et al.  Sketch-to-photo matching: a feature-based approach , 2010, Defense + Commercial Sensing.

[21]  Chunna Tian,et al.  Face Sketch Synthesis using E-HMM and Selective Ensemble , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.