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A smart clustering algorithm for photo set obtained from multiple digital cameras

机译:从多个数码相机获得的照片集的智能聚类算法

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The use of digital cameras is prevalent. Although the cost of digital photographs is low, managing numerous digital photos is burdensome to most users. An intelligent management tool for digital photos is needed. We propose a novel clustering algorithm for concurrent digital photos obtained from multiple cameras. Since previous photo clustering methods can be applied to a single camera, a group of photos obtained from different cameras cannot be classified to meet user preference. We newly define temporal/spatial combined clustering for the set of group photos taken from different cameras to solve this situation. We define a new spatial similarity using block alignment for two independent photos. If a user submits photo clustering that shows preference between spatial and temporal clustering, then we can cluster other photo sets according to the reference clustering characteristics. In this method, the EXIF metadata plays an essential role. We tested more than one thousand photos taken by tourist groups. The final result was satisfactory compared to previous methods based on temporal (spatial) criteria only.
机译:使用数码相机是普遍的。虽然数字照片的成本很低,但管理众多数字照片对大多数用户来说都是繁重的。需要一种用于数码照片的智能管理工具。我们提出了一种用于从多个摄像机获得的并发数字照片的新型聚类算法。由于先前的照片聚类方法可以应用于单个相机,因此无法对从不同摄像机获得的一组照片进行分类以满足用户偏好。我们新定义了从不同摄像机拍摄的一组群体照片的时间/空间组合聚类以解决这种情况。我们使用两个独立照片的块对齐方式定义新的空间相似度。如果用户提交照片群集,则在空间和时间群集之间显示首选项,那么我们可以根据参考群集特征群集其他照片集。在此方法中,EXIF元数据发挥着重要作用。我们测试了旅游群体拍摄的一千多张。与基于时间(空间)标准的先前方法相比,最终结果令人满意。

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