Abstract
Object categorization is an important problem in computer vision. The bag-of-words approach has gained much research in object categorization, which has shown state-of-art performance. This bag-of-words(BOW) approach ignores spatial relationship between local features. But local features in most classes have spatial dependence in real world. So we propose a novel object categorization model with implicit local spatial relationship based on bag-of-words model(BOW with ILSR). The model use neighbor features of one local feature as its implicit local spatial relationship, which is integrated with its appearance feature to form two sources of information for categorization. The characteristic of the model can not only preserve some degree of flexibility, but also incorporate necessary spatial information. The algorithm is applied in Caltech-101 and Caltech-256 datasets to validate its efficiency. The experimental results show its good 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
Szummer, M., Picard, R.W.: Indoor-outdoor image classification. In: ICCV Workshop on Content-based Access of Image and Video Databases, Bombay, India, pp. 42–50 (1998)
Vailaya, A., Figueiredo, A., Jain, A., Zhang, H.: Image classification for content-based indexing. Transactions on Image Processing, 117–129 (2001)
Vogel, J., Schiele, B.: Natural Scene Retrieval Based on a Semantic Modeling Step. In: Enser, P.G.B., Kompatsiaris, Y., O’Connor, N.E., Smeaton, A., Smeulders, A.W.M. (eds.) CIVR 2004. LNCS, vol. 3115, pp. 207–215. Springer, Heidelberg (2004)
Harris, C., Stevens, M.: A combined corner and edge detector. In: Proceedings of the 4th Alvey Vision Conference, pp. 147–151 (1988)
Lowe, D.G.: Object recognition from local scale-invariant features. In: Proceedings of the 7th International Conference on Computer Vision, Kerkyra, Greece, pp. 1150–1157 (1999)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60(2), 191–210 (2004)
Fergus, R., Perona, P., Zisserman, A.: Object class recognition by unsupervised scale-invariant learning. In: Proceedings of the IEEE International Conference on Computer Vision, vol. 2, pp. 264–271 (2003)
Crandall, D., Felzenszwalb, P., Huttenlocher, D.: Spatial priors for part-based recognition using statistical models. In: IEEE International Conference on Computer Vision, pp. 10–17 (2005)
Bouchard, G., Triggs, B.: Hierarchical part-based visual object categorization. In: IEEE International Conference on Computer Vision, vol. 1, pp. 710–715 (2005)
Felzenszwalb, P., Huttenlocher, D.: Pictorial structures for object recognition. International Journal of Computer Vision 61(1), 55–79 (2005)
Csurka, G., Bray, C., Dance, C., Fan, L.: Visual categorization with bags of keypoints. In: Workshop on Statistical Learning in Computer Vision, European Conference on Computer Vision, pp. 1–22 (2004)
Li, F.F., Perona, P.: A Bayesian hierarchical model for learning natural scene categories. In: IEEE International Conference on Computer Vision, vol. 2, pp. 524–531 (2005)
Sivic, J., Russell, B., Efros, A., Zisserman, A., Freeman, W.: Discovering object categories in image collections. Technical Report, Massachusetts Institute of Technology (2005)
Ullman, S., Naquet, M.V., Sali, E.: Visual features of intermediate complexity and their use in classification. Nature Neurosci. 5(7), 682–687 (2002)
Cula, O.G., Dana, K.J.: Recognition Methods for 3D Textured Surfaces. In: Proceedings of SPIE Conference on Human Vision and Electronic Imaging VI, San Jose, California, pp. 209–220 (2001)
Blei, D., Ng, A., Jordan, M.: Latent Dirichlet allocation. Journal of Machine Learning Research 3, 993–1022 (2003)
Aksoy, S., Koperski, K., Tusk, C., Marchisio, G., Tilton, J.C.: Learning Bayesian classifiers for scene classification with a visual grammar. IEEE Transactions on Geoscience and Remote Sensing 43(3), 581–589 (2005)
Bloch, I.: Fuzzy spatial relationships for image processing and interpretation: A review. Image and Vision Computing 23(2), 89–110 (2005)
Boutell, M.R., Luo, J., Brown, C.M.: Factor graphs for region-based whole-scene classification. In: IEEE Conference on Computer Vision and Pattern Recognition, SLAM Workshop, New York (2006)
Kumar, S., Hebert, M.: A hierarchical field framework for unified context-based classification. In: IEEE International Conference on Computer Vision, Beijing, China, vol. 2, pp. 1284–1291 (2005)
Marszalek, M., Schmid, C.: Spatial Weighting for Bag-of-Features. In: Proceedings of the IEEE International Conference on Computer Vision, vol. 2, pp. 2118–2125 (2006)
Gökalp, D., Aksoy, S.: Scene Classification Using Bag-of-Regions Representations. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1–8 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wu, L., Luo, S., Sun, W. (2010). A Novel Object Categorization Model with Implicit Local Spatial Relationship. In: Zhang, L., Lu, BL., Kwok, J. (eds) Advances in Neural Networks - ISNN 2010. ISNN 2010. Lecture Notes in Computer Science, vol 6064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13318-3_18
Download citation
DOI: https://doi.org/10.1007/978-3-642-13318-3_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13317-6
Online ISBN: 978-3-642-13318-3
eBook Packages: Computer ScienceComputer Science (R0)