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Kang et al., 2009 - Google Patents

Image matching in large scale indoor environment

Kang et al., 2009

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Document ID
10702798261882686815
Author
Kang H
Efros A
Hebert M
Kanade T
Publication year
Publication venue
2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

External Links

Snippet

In this paper, we propose a data driven approach to first-person vision. We propose a novel image matching algorithm, named Re-Search, that is designed to cope with self-repetitive structures and confusing patterns in the indoor environment. This algorithm uses state-of-art …
Continue reading at kilthub.cmu.edu (PDF) (other versions)

Classifications

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    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30781Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F17/30784Information 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
    • G06F17/30799Information 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
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    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30244Information retrieval; Database structures therefor; File system structures therefor in image databases
    • G06F17/30247Information retrieval; Database structures therefor; File system structures therefor in image databases based on features automatically derived from the image data
    • G06F17/30256Information 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6201Matching; Proximity measures
    • G06K9/6202Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
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    • G06K9/62Methods or arrangements for recognition using electronic means
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    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • G06K9/4671Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
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    • G06F17/3061Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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    • G06F17/3071Clustering or classification including class or cluster creation or modification
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    • G06K9/00221Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
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