Parallel Multi-task Cascade Convolution Neural Network Optimization Algorithm for Real-time Dynamic Face Recognition |
Jiang, Bin
(College of Electronic and Optical Engineering & College of Microelectronics, NJUPT)
Ren, Qiang (College of Electronic and Optical Engineering & College of Microelectronics, NJUPT) Dai, Fei (College of Telecommunications and Information Engineering, NJUPT) Zhou, Tian (College of Telecommunications and Information Engineering, NJUPT) Gui, Guan (College of Telecommunications and Information Engineering, NJUPT) |
1 | Y. Ren, Z. Wang, and M. Xu, "Learning-based saliency detection of face images," IEEE Access, vol. 5, pp. 6502-6514, 2017. DOI |
2 | G. Ghinea, R. Kannan, and S. Kannaiyan, "Gradient-orientation-based PCA subspace for novel face recognition," IEEE Access, vol. 2, pp. 914-920, 2014. DOI |
3 | M. Mei, J. Huang, and W. Xiong, "A discriminant subspace learning based face recognition method," IEEE Access, vol. 6, pp. 13050-13056, 2017. DOI |
4 | M. Z. Uddin, M. M. Hassan, A. Almogren, A. Alamri, M. Alrubaian, and G. Fortino, "Facial Expression Recognition Utilizing Local Direction-Based Robust Features and Deep Belief Network," IEEE Access, vol. 5, pp. 4525-4536, 2017. DOI |
5 | Y. Ding, Q. Zhao, B. Li, and X. Yuan, "Facial expression recognition from image sequence based on LBP and Taylor expansion," IEEE Access, vol. 5, pp. 19409-19419, 2017. DOI |
6 | M. Matsugu, K. Mori, M. Ishii, and Y. Mitarai, "Convolutional spiking neural network model for robust face detection," in Proc. of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02., vol. 2, pp. 660-664, 2002. |
7 | X. Zhang, M. Peng, and T. Chen, "Face recognition from near-infrared images with convolutional neural network," in Proc. of International Conference on Wireless Communications & Signal Processing, pp. 1-5, 2016. |
8 | P. Viola and M. J. Jones, "Robust real-time face detection," Int. J. Comput. Vis., vol. 57, no. 2, pp. 137-154, May 2004. DOI |
9 | H. Wu, K. Zhang, and G. Tian, "Simultaneous face detection and pose estimation using convolutional neural network cascade," IEEE Access, vol. 6, pp. 49563-49575, 2018. DOI |
10 | W. Zhao et al., "Superpixel-based multiple local CNN for panchromatic and multispectral image classification," IEEE Trans. Geosci. Remote Sens., vol. 55, no. 7, pp. 4141-4156, 2017. DOI |
11 | Y. Sun, X. Wang, and X. Tang, "Deep convolutional network cascade for facial point detection," in Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3476-3483, 2013. |
12 | G. Li, Haoxiang and Lin, Zhe and Shen, Xiaohui and Brandt, Jonathan and Hua, "A convolutional neural network cascade for face detection," in Proc. of 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5325-5334, 2015. |
13 | D. Chen, S. Ren, Y. Wei, X. Cao, and J. Sun, "Joint cascade face detection and alignment," Lect. Notes Comput. Sci., vol. 8694 LNCS, no. PART 6, pp. 109-122, 2014. |
14 | X. Li et al., "DeepSaliency: Multi-task deep neural network model for salient object detection," IEEE Trans. Image Process., vol. 25, no. 8, pp. 3919-3930, 2016. DOI |
15 | H. Liu, J. Lu, J. Feng, and J. Zhou, "Two-stream transformer networks for video-based face alignment," IEEE Trans. Pattern Anal. Mach. Intell., vol. 40, no. 11, pp. 2546-2554, 2018. DOI |
16 | X. Yu, J. Huang, S. Zhang, W. Yan, and D. N. Metaxas, "Pose-free facial landmark fitting via optimized part mixtures and cascaded deformable shape model," in Proc. of 2013 IEEE International Conference on Computer Vision (ICCV), pp. 1944-1951, 2013. |
17 | E. Zhou, H. Fan, Z. Cao, Y. Jiang, and Q. Yin, "Extensive facial landmark localization with coarse-to-fine convolutional network cascade," in Proc. of IEEE International Conference on Computer Vision Workshops, pp. 386-391, 2013. |
18 | B. Shi, X. Bai, W. Liu, and J. Wang, "Face alignment with deep regression," IEEE Trans. Neural Networks Learn. Syst., vol. 29, no. 1, pp. 183-194, 2018. DOI |
19 | Yizhang Xia, Bailing Zhang, and F. Coenen, "Face occlusion detection based on multi-task convolution neural network," in Proc. of 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp. 375-379, 2015. |
20 | H. A. Elsalamony, "Automatic video stream indexing and retrieving based on face detection using wavelet transformation," in Proc. of 2010 2nd International Conference on Signal Processing Systems, vol. 1, pp. V1-153-V1-157, 2010. |
21 | S. Ding, Y. Li, J. Zhu, Y. F. Zheng, and D. Xuan, "Sequential sample consensus: A robust algorithm for video-based face recognition," IEEE Trans. Circuits Syst. Video Technol., vol. 25, no. 10, pp. 1586-1598, 2015. DOI |
22 | S. Yang, P. Luo, C. C. Loy, and X. Tang, "Faceness-Net: Face detection through deep facial part responses," IEEE Trans. Pattern Anal. Mach. Intell., vol. 40, no. 8, pp. 1845-1859, 2018. DOI |
23 | F. Schroff, D. Kalenichenko, and J. Philbin, "FaceNet: A unified embedding for face recognition and clustering," in Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 815-823, 07-12-June 2015. |
24 | K. Heath and L. Guibas, "Facenet: Tracking people and acquiring canonical face images in a wireless camera sensor network," in Proc. of 2007 First ACM/IEEE International Conference on Distributed Smart Cameras, pp. 117-124, 2007. |
25 | M. A. Abuzneid and A. Mahmood, "Enhanced human face recognition using LBPH descriptor, multi-KNN, and back-propagation neural network," IEEE Access, vol. 6, pp. 20641-20651, 2018. DOI |
26 | J. Ma, L. Zhang, S. Zhang, and X. Yao, "Vulnerability analysis of the optical network NMS," International Conference on Instrumentation, Measurement, Computer, Communication and Control, pp. 1185-1187, 2012. |
27 | Kuang-Chih Lee, J. Ho, Ming-Hsuan Yang, and D. Kriegman, "Video-based face recognition using probabilistic appearance manifolds," in Proc. of 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. I-313-I-320, 2003. |
28 | B. Liu, W. Zhao, and Q. Sun, "Study of object detection based on Faster R-CNN," in Proc. of 2017 Chinese Automation Congress (CAC), pp. 6233-6236, 2017. |
29 | W. Sibanda and P. Pretorius, "Comparative study of the application of central composite face-centred (CCF) and Box-Behnken designs (BBD) to study the effect of demographic characteristics on HIV risk in South Africa," Netw. Model. Anal. Heal. Informatics Bioinforma., vol. 2, no. 3, pp. 137-146, Sep. 2013. DOI |
30 | C. Su and C. Tseng, "L1/L2 difference in phonological sensitivity and information planning — Evidence from F0 patterns," in Proc. of 2016 10th International Symposium on Chinese Spoken Language Processing (ISCSLP), pp. 1-5, 2016. |
31 | V. Jain, E. Learned-Miller, "FDDB: A benchmark for face detection in unconstrained settings," UMass Amherst Technical Report, 2010. |
32 | S. Z. Li, D. Yi, Z. Lei, and S. Liao, "The CASIA NIR-VIS 2.0 face database," in Proc. of IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 348-353, 2013. |
33 | Q. Liu and C. Liu, "A novel locally linear KNN model for visual recognition," in Proc. of 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1329-1337, 2015. |
34 | F. Wang, W. Zuo, L. Zhang, D. Meng, and D. Zhang, "A kernel classification framework for metric learning," IEEE Trans. Neural Networks Learn. Syst., vol. 26, no. 9, pp. 1950-1962, Sep. 2015. DOI |
35 | Z. Ma, J.-H. Xue, A. Leijon, Z.-H. Tan, Z. Yang, and J. Guo, "Decorrelation of neutral vector variables: Theory and applications," IEEE Trans. Neural Networks Learn. Syst., vol. 29, no. 1, pp. 129-143, Jan. 2018. DOI |
36 | S. Pang, D. Kim, and S. Y. Bang, "Face membership authentication using SVM classification tree generated by membership-based LLE data partition," IEEE Trans. Neural Networks, vol. 16, no. 2, pp. 436-446, 2005. DOI |
37 | T. Zhou, S. Yang, L. Wang, J. Yao, and G. Gui, "Improved cross-label suppression dictionary learning for face recognition," IEEE Access, vol. 6, pp. 48716-48725, 2018. DOI |
38 | Z. Jiang, Z. Lin, and L. S. Davis, "Label consistent K-SVD: Learning a discriminative dictionary for recognition," IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 11, pp. 2651-2664, Nov. 2013. DOI |
39 | D. Wang and S. Kong, "A classification-oriented dictionary learning model: Explicitly learning the particularity and commonality across categories," Pattern Recognit., vol. 47, no. 2, pp. 885-898, Feb. 2014. DOI |
40 | X. Wang and Y. Gu, "Cross-label suppression: A discriminative and fast dictionary learning with group regularization," IEEE Trans. Image Process., vol. 26, no. 8, pp. 3859-3873, Aug. 2017. DOI |
41 | Z. Ma, A. E. Teschendorff, A. Leijon, Y. Qiao, H. Zhang, and J. Guo, "Variational Bayesian matrix factorization for bounded support data," IEEE Trans. Pattern Anal. Mach. Intell., vol. 37, no. 4, pp. 876-889, Apr. 2015. DOI |
42 | Z. Ma et al., "IEEE Access special section editorial: Recent advantages of computer vision," IEEE Access, vol. 6, pp. 31481-31485, 2018. DOI |
43 | K. Zhang, Z. Zhang, Z. Li, and Y. Qiao, "Joint face detection and alignment using multitask cascaded convolutional networks," IEEE Signal Process. Lett., vol. 23, no. 10, pp. 1499-1503, Oct. 2016. DOI |
44 | Y. Goh, Z. Ho, C. Ng, and Y. Goh, "Enhanced CNN-based plant growing-stage classification using additional information carried in an additional channel," IEIE Transactions on Smart Processing & Computing, vol. 8, no. 3, pp.171-177, June, 2019. DOI |