Abstract
In this chapter, some classic classifiers which are based on sparse representation are outlined. First, it describes the sparse representation-based classifier (SRC) which is very useful in human face recognition. Then, it includes spatial pyramid matching sparse coding method which replaces the vector quantization method and it is widely used in scene recognition. Third, it describes the sparsity-based nearest neighbor classifiers and sparse coding-based deformable part models which improve the performance of deformable part model.
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
Behmo, R., Marcombes, P., Dalalyan, A., Prinet, V.: Towards optimal naive bayes nearest neighbor. In: ECCV. Springer, Heidelberg (2010)
Boiman, O., Shechtman, E., Irani, M.: Defense of nearest-neighbor based image classification. In: IEEE CVPR (2008)
Boix, X., Roig, G., Leistner, C., Van Gool, L.: Nested sparse quantization for efficient feature coding. In: ECCV. Springer, Berlin (2012)
Boureau, Y.L., Ponce, J., LeCun, Y.: A theoretical analysis of feature pooling in visual recognition. In: Proceedings of the 27th International Conference on Machine Learning (2010)
Cevikalp, H., Triggs, B.: Face recognition based on image sets. In: IEEE CVPR (2010)
Cheng, H., Liu, Z., Hou, L., Yang, J.: Sparsity induced similarity measure and its applications. IEEE Trans. Circuits Syst. Video Technol (2012)
Cheng, H., Liu, Z., Yang, L.: Sparsity induced similarity measure for label propagation. In: IEEE ICCV (2009)
Cheng, H., Yu, R., Liu, Z., Liu, Y.: A pyramid nearest neighbor search Kernel for object categorization. In: IEEE ICPR (2012)
Fei-Fei, L., Perona, P.: A bayesian hierarchical model for learning natural scene categories. In: IEEE CVPR (2005)
Felzenszwalb, P., McAllester, D., Ramanan, D.: A discriminatively trained, multiscale, deformable part model. In: IEEE CVPR (2008)
Felzenszwalb, P.F., Huttenlocher, D.P.: Pictorial structures for object recognition. Int. J. Comput. Vis. 61(1), 55–79 (2005)
Gao, S., Tsang, I.W., Chia, L.T., Zhao, P.: Local features are not lonely-Laplacian sparse coding for image classification. In: IEEE CVPR (2010)
Gao, S., Tsang, I.W.H., Chia, L.T.: Kernel sparse representation for image classification and face recognition. In: ECCV (2010)
Hu, Y., Mian, A.S., Owens, R.: Sparse approximated nearest points for image set classification. In: IEEE CVPR (2011)
Lazebnik, S., Schmid, C., Ponce, J.: Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In: IEEE CVPR (2006)
Lee, H., Battle, A., Raina, R., Ng, A.Y.: Efficient sparse coding algorithms. Adv. Neural Inf. Process. Syst. 19, 801 (2007)
Nowak, E., Jurie, F., Triggs, B.: Sampling strategies for bag-of-features image classification. In: ECCV. Springer, Heidelberg (2006)
Shi, Q., Li, H., Shen, C.: Rapid face recognition using hashing. In: IEEE CVPR (2010)
Song, H.O., Zickler, S., Althoff, T., Girshick, R., Fritz, M., Geyer, C., Felzenszwalb, P., Darrell, T.: Sparselet models for efficient multiclass object detection. In: ECCV. Springer, Berlin (2012)
Wang, J., Yang, J., Yu, K., Lv, F., Huang, T., Gong, Y.: Locality-constrained linear coding for image classification. In: IEEE CVPR (2010)
Wright, J., Yang, A.Y., Ganesh, A., Sastry, S.S., Ma, Y.: Robust face recognition via sparse representation. IEEE Trans. Pattern Anal. Mach. Intell. 31(2), 210–227 (2009)
Yang, J., Yu, K., Gong, Y., Huang, T.: Linear spatial pyramid matching using sparse coding for image classification. In: IEEE CVPR (2009)
Zhang, D., Yang, M., Feng, X.: Sparse representation or collaborative representation: which helps face recognition? In: IEEE ICCV (2011)
Zhang, L., Zhou, W.D., Chang, P.C., Liu, J., Yan, Z., Wang, T., Li, F.Z.: Kernel sparse representation-based classifier. IEEE Trans. Signal Process. 60(4), 1684–1695 (2012)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2015 Springer-Verlag London
About this chapter
Cite this chapter
Cheng, H. (2015). Sparse Representation and Learning-Based Classifiers. In: Sparse Representation, Modeling and Learning in Visual Recognition. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-6714-3_8
Download citation
DOI: https://doi.org/10.1007/978-1-4471-6714-3_8
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-6713-6
Online ISBN: 978-1-4471-6714-3
eBook Packages: Computer ScienceComputer Science (R0)