基于嵌套聚类的拍照点推荐

Kosuke Kimura, Hung-Hsuan Huang, K. Kawagoe
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引用次数: 2

摘要

在本文中,我们提出了一种新的从大量的社会社区照片中推荐拍照点的方法。从Flickr、Picas和Panoramio等照片共享web服务存储和管理的大量照片中,有很多与照片相关的推荐研究活动,虽然已经提出了一些方法,如地标推荐、标签推荐和照片推荐,但目前还没有实现针对社交照片收藏的拍照点推荐方法。为了实现拍照点推荐,提出了一种新的基于嵌套聚类的拍照点和照片选择方法。实验结果表明,该方法具有较好的推荐精度。
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Photo-Taking Point Recommendation with Nested Clustering
In this paper, we propose a novel recommendation method for photo-taking points from a large amount of social community photo collections. There are many research activities on photo-related recommendations from a lot of photos stored and managed by photo sharing web services, such as Flickr, Picas a and Panoramio, Although some methods, such as landmark recommendation, tag recommendation and photo recommendation have already been proposed, no photo-taking point recommendation methods have been realized yet for social photo collections. In order to realize photo-taking point recommendation, we introduce a novel point and photo selection method based on nested clustering. From our experiments, it is shown that better recommendation accuracy with our proposed method can be attained.
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