Abstract
This chapter presents a robust face recognition technique which is based on the extraction of Scale Invariant Feature Transform (SIFT) features from the face areas. It uses both a global and local matching strategy. The local strategy is based on matching individual salient facial SIFT features as connected to facial landmarks such as the eyes and the mouth. As for the global matching strategy, all SIFT features are combined together to form a single feature. The Dempster–Shafer decision theory is applied to fuse the two matching strategies. The proposed technique has been evaluated with the Indian Institute of Technology Kanpur (IITK), Olivetti Research Laboratory (ORL) (formerly known as AT&T face database), and the Yale face databases. The experimental results demonstrate the effectiveness and potential of the proposed face recognition technique also in cases of partially occluded faces or with missing information. Besides this, some state-of-the-art face recognition techniques have been presented and the current face-matching technique is compared with those techniques while all the matching techniques use SIFT descriptors as local features.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Shakhnarovich, G., Moghaddam, B.: Face recognition in subspaces. In Li, S., Jain, A. (eds), Handbook of Face Recognition, pp. 141–168, Springer Verlag (2004).
Shakhnarovich, G., Fisher, J.W., Darrell, T.: Face recognition from long-term observations. IEEE European Conference on Computer Vision, 851–865 (2002).
Wiskott, L., Fellous, J., Kruger, N., Malsburg, C.: Face recognition by elastic bunch graph matching. IEEE Transactions on Pattern Analysis and Machine Intelligence, 775–779 (1997).
Bigun, J.: Retinal vision applied to facial features detection and face authentication. Pattern Recognition Letters, 23(4), 463–475 (1997).
Zhang, G., Huang, X., Li, S., Wang, Y., Wu, X.: Boosting local binary pattern (lbp)-based face recognition, SINOBIOMETRICS, 179–186 (2004).
Heusch, G., Rodriguez, Y., Marcel, S.: Local binary patterns as an image preprocessing for face authentication. IDIAP-RR 76, IDIAP (2005).
Kisku, D.R., Rattani, A., Grosso, E., Tistarelli, M.: Face identification by SIFT-based complete graph topology. IEEE Workshop AutoId, 63–68 (2007).
Lowe, D.: Object recognition from local scale-invariant features. International Conference on Computer Vision, 1150–1157 (1999).
Lowe, D.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2), 91–110 (2004).
Park, U., Pankanti, S., Jain, A.K.: Fingerprint verification using SIFT features. SPIE, Security and Defense.6944, 69440K-69440K-9 (2008).
Smeraldi, F., Capdevielle, N., Bigün, J.: Facial features detection by saccadic exploration of the Gabor decomposition and Support Vector Machines. 11th Scandinavian Conference on Image Analysis 1, 39–44 (1999).
Gourier, N., James, D.H., Crowley, L.: Estimating face orientation from robust detection of salient facial structures. FG Net Workshop on Visual Observation of Deictic Gestures (2004).
Snelick, R., Uludag, U., Mink, A., Indovina, M., Jain, A.: Large scale evaluation of multimodal biometric authentication using state-of-the-art systems. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(3), 450–455 (2005).
Samaria, F., Harter, A.: Parameterization of a stochastic model for human face iden tification. IEEE Workshop on Applications of Computer Vision (1994).
http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html
Tan, K., Chen, S.: Adaptively weighted sub-pattern PCA for face recognition. Neurocomputing 64, 505–511 (2005).
Yale face database. http://cvc.yale.edu
Kisku, D.R., Rattani, A., Grosso, E., Tistarelli, M.: Face Identification by SIFT-based Complete Graph Topology. 5th IEEE International Workshop on Automatic Identification Advanced Technologies, 63–68 (2007).
Kisku, D.R., Rattani, A., Tistarelli, M., Gupta, P.: Graph Application on Face for Personal Authentication and Recognition. 10th IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV), 1150–1155 (2008).
Bicego, M., Lagorio, A., Grosso, E., Tistarelli, M.: On the use of SIFT features for face authentication. IEEE International Workshop on Biometrics, in association with CVPR (2006).
Majumdar, A., Ward, R.K.: Discriminative SIFT features for face recognition. IEEE Canadian Conference on Electrical and Computer Engineering, 27–30 (2009).
Luo, J., Ma, Y., Takikawa, E., Lao, S., Kawade, M., Lu, B.-L.: Person-specific sift features for face recognition. IEEE Conference on Acoustics, Speech and Signal Processing, 593–596 (2007)
Kisku, D. R., Tistarelli, M., Sing, J.K., Gupta, P.: Face Recognition by Fusion of Local and Global Matching Scores using DS Theory: An Evaluation with Uni-classifier and Multi-classifier Paradigm. 3rd IEEE Computer Vision and Pattern Recognition Workshop on Biometrics (CVPR), 60–65 (2009).
Mian, A., Bennamoun, M., Owens, R.: Face recognition using 2D and 3D multimodal local features. International Symposium on Computer Vision, 860–870 (2006).
Wang, Z., Miao, Z.: Scale invariant face recognition using probabilistic similarity measure, International Conference on Pattern Recognition, 1–4 (2008).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag London Limited
About this chapter
Cite this chapter
Kisku, D.R., Gupta, P., Sing, J.K., Tistarelli, M. (2011). Face Recognition Using Global and Local Salient Features. In: Yang, X., Wang, L., Jie, W. (eds) Guide to e-Science. Computer Communications and Networks. Springer, London. https://doi.org/10.1007/978-0-85729-439-5_16
Download citation
DOI: https://doi.org/10.1007/978-0-85729-439-5_16
Published:
Publisher Name: Springer, London
Print ISBN: 978-0-85729-438-8
Online ISBN: 978-0-85729-439-5
eBook Packages: Computer ScienceComputer Science (R0)