Abstract
Recently, codebook-based object recognition methods have achieved the state-of-the-art performances for many public object databases. Based on the codebook-based object recognition method, we propose a novel method which uses the saliency information in the stage of pooling code vectors. By controlling each code response using the saliency value that represents the visual importance of each local area in an image, the proposed method can effectively reduce the adverse influence of low visual saliency regions, such as the background. On the basis of experiments on the public Flower102 database and Caltech object database, we confirm that the proposed method can improve the conventional codebook-based methods.
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Acknowledgments
This research was partially supported by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC(Information Technology Research Center) support program (NIPA-2012- H0301-12-2004) supervised by the NIPA(National IT Industry Promotion Agency); and by the Converging Research Center Program funded by the Ministry of Education, Science and Technology (2012K001342).
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© 2013 Springer Science+Business Media Dordrecht(Outside the USA)
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Kim, DH., Lee, K., Park, H. (2013). Weighted Pooling of Image Code with Saliency Map for Object Recognition. In: Park, J., Ng, JY., Jeong, HY., Waluyo, B. (eds) Multimedia and Ubiquitous Engineering. Lecture Notes in Electrical Engineering, vol 240. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6738-6_20
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DOI: https://doi.org/10.1007/978-94-007-6738-6_20
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