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Aly et al., 2011 - Google Patents

Indexing in large scale image collections: Scaling properties and benchmark

Aly et al., 2011

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Document ID
9819381868498042466
Author
Aly M
Munich M
Perona P
Publication year
Publication venue
2011 IEEE Workshop on Applications of Computer Vision (WACV)

External Links

Snippet

Indexing quickly and accurately in a large collection of images has become an important problem with many applications. Given a query image, the goal is to retrieve matching images in the collection. We compare the structure and properties of seven different …
Continue reading at citeseerx.ist.psu.edu (PDF) (other versions)

Classifications

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    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
    • G06F17/30247—Information retrieval; Database structures therefor; File system structures therefor in image databases based on features automatically derived from the image data
    • G06F17/30256—Information retrieval; Database structures therefor; File system structures therefor in image databases based on features automatically derived from the image data using a combination of image content features
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
    • G06K9/4676—Extracting features based on a plurality of salient regional features, e.g. "bag of words"
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    • G06K9/62—Methods or arrangements for recognition using electronic means
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    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G06K9/627—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches based on distances between the pattern to be recognised and training or reference patterns
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    • G06F17/30799—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre using low-level visual features of the video content
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