MIL at ImageCLEF 2013: Personal Photo Retrieval
نویسندگان
چکیده
In this paper, we describe our methods for ImageCLEF 2013 Personal Photo Retrieval Task. We devote our attention to making our system efficient in retrieving documents which have the similar topic with few query data. We train a ranking function using rankSVM. We extract Fisher Vectors (FVs) from several local descriptors as visual features, and use Bag-of-Words (BoW) as metadata features. The final similarity score is the weighted average of the visual similarities and the metadata similarities, where the weights are determined by relevance feedback. Results have shown that our system achieves the best performance in the Personal Photo Retrieval Task.
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