Abstract
We develop a framework for combining configurational and statistical approaches in image retrieval. While configurations have semantic description power, the explicit representation of an image by a set of configurations lacks the vector space structure from which the statistical feature-based representations have benefitted. That makes concept learning and prediction harder. Our framework treats configurations analogously to words occurring in a document. It combines a configuration-based approach with statistical approaches to take advantage of both the semantic description power of the former, and the simple vector-space structure of the latter.
This work is supported by ITRI.
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References
R.C. Bolles and R.A. Cain. Recognizing and Locating Partially Visible Objects. The International Journal of Robotics Research, Vol. 1, Num. 3, 1982.
M. Das, E. Riseman, and B. Draper. FOCUS: Searching for Multi-colored Objects in a Diverse Image Database, IEEE CVPR, 1997.
R. Haralick, and L. Shapiro. Computer and Robot Vision, Addison-Wesley, 1992.
A. Lakshmi Ratan, and W.E.L. Grimson. Training Templates for Scene Classification using a Few Examples, IEEE Workshop CAIVL, 1997.
P. Lipson. Context and Configuration Based Scene Classification, Ph.D. Thesis, MIT, 1996.
W.Y. Ma, and B. Manjunath. NeTra: A Toolbox for Navigating Large Image Databases. IEEE CVPR, 1997.
O. Maron, and A. Lakshmi Ratan. Multiple Instance Learning for Natural Scene Classification. The 11th ICML, 1998.
C. Nastar, M. Mitschke, and C. Meilhac. Efficient Query Refinement for Image Retrieval, IEEE CVPR, 1998.
J. Pearl. Probabilistic reasoning in intelligent systems: networks of plausible inference, Morgan Kaufmann, 1988.
K. Tieu and P. Viola. Boosting Image Retrieval, IEEE CVPR, 2000.
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© 2001 Springer-Verlag Berlin Heidelberg
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Yu, H., Grimson, W.E.L. (2001). Combining Configurational and Statistical Approaches in Image Retrieval. In: Shum, HY., Liao, M., Chang, SF. (eds) Advances in Multimedia Information Processing — PCM 2001. PCM 2001. Lecture Notes in Computer Science, vol 2195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45453-5_38
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DOI: https://doi.org/10.1007/3-540-45453-5_38
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