Temporal event clustering for digital photo collections
Temporal event clustering for digital photo collections
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DOI：
10.1145/957013.957093
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发表时间：
2003-11
期刊：
影响因子：
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通讯作者：
Matthew L. Cooper;J. Foote;Andreas Girgensohn;L. Wilcox
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文献类型：
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作者：
Matthew L. Cooper;J. Foote;Andreas Girgensohn;L. Wilcox
我们提出了基于相似性的方法来聚类的数字照片的时间和图像内容。该方法是通用的，无监督的，并对照片集的结构或统计数据做出最小的假设。我们目前的结果，该算法完全基于时间的相似性，并联合时间和基于内容的相似性。我们还描述了一种基于学习矢量量化的监督算法。最后，我们包括两个测试集合的实验结果，所提出的算法和几个竞争的方法。
We present similarity-based methods to cluster digital photos by time and image content. The approach is general, unsupervised, and makes minimal assumptions regarding the structure or statistics of the photo collection. We present results for the algorithm based solely on temporal similarity, and jointly on temporal and content-based similarity. We also describe a supervised algorithm based on learning vector quantization. Finally, we include experimental results for the proposed algorithms and several competing approaches on two test collections.