Abstract
Recognizing plant leaves has so far been a difficult and important work. In this paper, we formulate the problem of classifying leaf image sets rather than single-shot images, each of sets contain leaf images pertain to the same class. We compute the distance between two manifolds by modeling each leaf image set as a manifold. Specifically, we apply a clustering procedure in order to express a manifold by a collection of local linear models which are depicted by a subspace. Then the distance is measured between local models which come from different manifolds constructed above. Finally, the problem is transformed to integrate the distances between pairs of subspaces from one of the involved manifolds. Experiment based on the leaves (ICL) from intelligent computing laboratory of Chinese academy of sciences shows the method has great performance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Edelman, A., Arias, T.A., Smith, S.T.: The geometry of algorithms with orthogonality constraints. SIAM Journal on Matrix Analysis and Applications 20(2), 303–353 (1998)
Wolf, L., Shashua, A.: Learning over sets using kernel principal angles. The Journal of Machine Learning Research 4, 913–931 (2003)
Hu, Y., Mian, A.S., Owens, R.: Sparse approximated nearest points for image set classification. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 121–128 (2011)
Wang, R., Shan, S., Chen, X., Gao, W.: Manifold-manifold distance with application to face recognition based on image set. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)
Hamm, J., Lee, D.D.: Grassmann discriminant analysis: a unifying view on subspace-based learning. In: Proceedings of the 25th International Conference on Machine Learning, pp. 376–383 (2008)
Hotelling, H.: Relations between two sets of variates. Biometrika 28(3/4), 321–377 (1936)
Yamaguchi, O., Fukui, K., Maeda, K.I.: Face recognition using temporal image sequence. In: Proceedings of the Third IEEE International Conference on Automatic Face and Gesture Recognition, pp. 318–323 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Shao, MW., Du, JX., Wang, J., Zhai, CM. (2014). Recognition of Leaf Image Set Based on Manifold-Manifold Distance. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_36
Download citation
DOI: https://doi.org/10.1007/978-3-319-09333-8_36
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09332-1
Online ISBN: 978-3-319-09333-8
eBook Packages: Computer ScienceComputer Science (R0)