| 摘要 |
Systems and methods for clustering photos that include both time stamps and location coordinates. A two step method that first detects boundaries using time and location information independently to form a set of candidate boundaries is implemented. Such boundaries partition the set of time-ordered photos into clusters. A subset of the candidate boundaries is selected by an efficient dynamic programming procedure to optimize a cost function. Several cost functions are used to design clusterings that are coherent in space, time, or both. One set of cost functions minimizes inter-photo distances directly. A second set maximizes an information measure to select clusterings for consistency in both time and space.
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