Abstract
With emergence and development of Web2.0 and location-based technologies, location-based image retrieval and indexing has been increasingly paid much attention. In the state-of-the-art retrieval methods, geo-tag and visual feature-based image retrieval has not been touched so far. In this paper, we present an efficient location-based image retrieval method by conducting the search over combined geotag- and visual-feature spaces. In this retrieval method, a cost-based query optimization scheme is proposed to optimize the query processing. Different from conventional image retrieval methods, our proposed retrieval algorithm combines the above two features to obtain an uniform measure. Comprehensive experiments are conducted to testify the effectiveness and efficiency of our proposed retrieval and indexing methods respectively.
This paper is partially supported by the Program of National Natural Science Foundation of China under Grant No. 61003074, No. 61103229; The Program of Natural Science Foundation of Zhejiang Province under Grant No. Z1100822, No. Y1110644, Y1110969, No.Y1090165; The Science & Technology Planning Project of Wenzhou under Grant No. G20100202.
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Zhuang, Y., Jiang, G., Ding, J., Jiang, N., Zhu, G. (2013). Effective Location-Based Image Retrieval Based on Geo-Tags and Visual Features. In: Zhou, S., Wu, Z. (eds) Social Media Retrieval and Mining. Communications in Computer and Information Science, vol 387. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41629-3_12
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DOI: https://doi.org/10.1007/978-3-642-41629-3_12
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