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- W195272172 abstract "Landmark image mining and detection have been studied for many years, however, most of the existing work focuses on their spatial attributes, while largely ignoring the temporal information in specific ones, which are taken during historical moments. This kind of images are more valuable than the normal ones as they not only contain more comprehensive information to illustrate the landmarks in different moments, but also are useful in many real world applications, such as tour recommendation and history education. In this paper, we present a novel framework named Landmark History Visualization (LHV) to mine relevant and diverse images for each landmark’s historic moments. There are two steps in LHV. The first one is to extract the event list of each landmark from Wikipedia. The event keywords are extracted, and some of them are automatically labeled as 3W (What, Who, When). In the second step, images searched by the landmark name are firstly collected from Flickr and Google images. Secondly, we employ manifold ranking with detected 3W to retrieve the relevant images, and lastly, an outlier detection and diversification based re-ranking approach is introduced to provide users with various returned images. We implemented our approach on 6 landmarks and the results demonstrate the effectiveness of LHV." @default.
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- W195272172 date "2013-01-01" @default.
- W195272172 modified "2023-09-28" @default.
- W195272172 title "Landmark History Visualization" @default.
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- W195272172 doi "https://doi.org/10.1007/978-3-642-35728-2_12" @default.
- W195272172 hasPublicationYear "2013" @default.
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