Abstract
With the largely growing quantity of face images in the social networks and media, different face analyzing systems are developed to be employed in real-world situations such as face recognition, facial expression detection, or automated face tagging. Two demanding face-related applications are studied in this paper: facial attribute classification and face image retrieval. The main common issue with most of the attribute classifiers and face retrieval systems is that they fail to perform well under various facial expressions, pose variations, geometrical deformation, and photometric alterations. On one hand, the emerging role of deep CNNs (convolutional neural networks) has shown superior results in tasks like object recognition, face recognition, etc. On the other hand, their applications are yet to be more investigated in facial attribute classification and face retrieval. In this study, we compare the performance of shallow and deep facial descriptors in the two mentioned applications by proposing to exploit distinctive facial features from a very deep pre-trained CNN for attribute classification as well as constructing deep attribute-driven feature vectors for face retrieval. According to the results, the higher accuracy of the attribute classifiers and superior performance of the face retrieval system is demonstrated.
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References
Lv, Y., Ng, W.W., Zeng, Z., Yeung, D.S., Chan, P.P.: Asymmetric cyclical hashing for large scale image retrieval. IEEE Trans. Multimedia 17, 1225–1235 (2015)
Tang, J., Li, Z., Wang, M., Zhao, R.: Neighborhood discriminant hashing for large-scale image retrieval. IEEE Trans. Image Process. 24, 2827–2840 (2015)
Cao, X., Zhang, H., Guo, X., Liu, S., Meng, D.: SLED: semantic label embedding dictionary representation for multilabel image annotation. IEEE Trans. Image Process. 24, 2746–2759 (2015)
Murthy, V.N., Maji, S., Manmatha, R.: Automatic image annotation using deep learning representations. In: Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, pp. 603–606 (2015)
Zitnick, C.L., Vedantam, R., Parikh, D.: Adopting abstract images for semantic scene understanding. IEEE Trans. Pattern Anal. Mach. Intell. 38, 627–638 (2016)
Kotenko, J.: Facebook reveals we upload a whopping 350 million photos to the network daily. DigitalTrends.com (2013)
Kumar, N., Belhumeur, P., Nayar, S.: FaceTracer: a search engine for large collections of images with faces. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008. LNCS, vol. 5305, pp. 340–353. Springer, Heidelberg (2008). doi:10.1007/978-3-540-88693-8_25
Parkhi, O.M., Vedaldi, A., Zisserman, A.: Deep face recognition. In: British Machine Vision Conference, vol. 1, p. 6 (2015)
Agrawal, S., Khatri, P.: Facial expression detection techniques: based on viola and jones algorithm and principal component analysis. In: 2015 Fifth International Conference on Advanced Computing and Communication Technologies, pp. 108–112 (2015)
Zhang, Y., Tang, Z., Zhang, C., Liu, J., Lu, H.: Automatic face annotation in tv series by video/script alignment. Neurocomputing 152, 316–321 (2015)
Utsumi, Y., Sakano, Y., Maekawa, K., Iwamura, M., Kise, K.: Scalable face retrieval by simple classifiers and voting scheme. In: Ji, Q., Moeslund, T.B., Hua, G., Nasrollahi, K. (eds.) FFER 2014. LNCS, vol. 8912, pp. 99–108. Springer, Heidelberg (2015). doi:10.1007/978-3-319-13737-7_9
Wang, D., Jain, A.K.: Face retriever: pre-filtering the gallery via deep neural net. In: 2015 International Conference on Biometrics (ICB), pp. 473–480 (2015)
Wang, D., Hoi, S.C., He, Y., Zhu, J., Mei, T., Luo, J.: Retrieval-based face annotation by weak label regularized local coordinate coding. IEEE Trans. Pattern Anal. Mach. Intell. 36, 550–563 (2014)
Smith, B.M., Zhu, S., Zhang, L.: Face image retrieval by shape manipulation. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 769–776 (2011)
Wu, Z., Ke, Q., Sun, J., Shum, H.Y.: Scalable face image retrieval with identity-based quantization and multireference reranking. IEEE Trans. Pattern Anal. Mach. Intell. 33, 1991–2001 (2011)
Park, U., Jain, A.K.: Face matching and retrieval using soft biometrics. IEEE Trans. Inf. Forensics Secur. 5, 406–415 (2010)
An, L., Zou, C., Zhang, L., Denney, B.: Scalable attribute-driven face image retrieval. Neurocomputing 172, 215–224 (2016)
Chen, B.C., Chen, Y.Y., Kuo, Y.H., Hsu, W.H.: Scalable face image retrieval using attribute-enhanced sparse codewords. IEEE Trans. Multimedia 15, 1163–1173 (2013)
Liu, Z., Luo, P., Wang, X., Tang, X.: Deep learning face attributes in the wild. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3730–3738 (2015)
Klare, B.F., Klum, S., Klontz, J.C., Taborsky, E., Akgul, T., Jain, A.K.: Suspect identification based on descriptive facial attributes. In: 2014 IEEE International Joint Conference on Biometrics (IJCB), pp. 1–8 (2014)
Rudd, E., Günther, M., Boult, T.: Moon: a mixed objective optimization network for the recognition of facial attributes. arXiv preprint arXiv:1603.07027 (2016)
Chen, B.C., Kuo, Y.H., Chen, Y.Y., Chu, K.Y., Hsu, W.: Semi-supervised face image retrieval using sparse coding with identity constraint. In: Proceedings of the 19th ACM International Conference on Multimedia, pp. 1369–1372 (2011)
Li, Y., Wang, R., Liu, H., Jiang, H., Shan, S., Chen, X.: Two birds, one stone: jointly learning binary code for large-scale face image retrieval and attributes prediction. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3819–3827 (2015)
Huang, G.B., Ramesh, M., Berg, T., Learned-Miller, E.: Labeled faces in the wild: a database for studying face recognition in unconstrained environments. Technical report 07–49, University of Massachusetts, Amherst (2007)
Viola, P., Jones, M.J.: Robust real-time face detection. Int. J. Comput. Vis. 57, 137–154 (2004)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), vol. 1, pp. 886–893 (2005)
Déniz, O., Bueno, G., Salido, J., De la Torre, F.: Face recognition using histograms of oriented gradients. Pattern Recogn. Lett. 32, 1598–1603 (2011)
Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24, 971–987 (2002)
Yang, B., Chen, S.: A comparative study on local binary pattern (LBP) based face recognition: LBP histogram versus LBP image. Neurocomputing 120, 365–379 (2013)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60, 91–110 (2004)
Vedaldi, A., Fulkerson, B.: VLFeat: an open and portable library of computer vision algorithms. In: Proceedings of the 18th ACM International Conference on Multimedia, pp. 1469–1472 (2010)
Acknowledgment
This research was fully funded by the Ministry of Science, Technology, and Innovation (MOSTI), Malaysia, Project Number 01-02-01-SF0232. We also gratefully acknowledge the feedback from anonymous reviewers.
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Banaeeyan, R., Lye, M.H., Fauzi, M.F.A., Karim, H.A., See, J. (2017). Deep or Shallow Facial Descriptors? A Case for Facial Attribute Classification and Face Retrieval. In: Chen, CS., Lu, J., Ma, KK. (eds) Computer Vision – ACCV 2016 Workshops. ACCV 2016. Lecture Notes in Computer Science(), vol 10117. Springer, Cham. https://doi.org/10.1007/978-3-319-54427-4_32
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