Matching sets of features for efficient retrieval and recognition

@inproceedings{Grauman2006MatchingSO,
  title={Matching sets of features for efficient retrieval and recognition},
  author={Kristen Grauman},
  year={2006}
}
In numerous domains it is useful to represent a single example by the collection of local features or parts that comprise it. In computer vision in particular, local image features are a powerful way to describe images of objects and scenes. Their stability under variable image conditions is critical for success in a wide range of recognition and retrieval applications. However, many conventional similarity measures and machine learning algorithms assume vector inputs. Comparing and learning… CONTINUE READING
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