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Favorskaya et al., 2016 - Google Patents

Fast salient object detection in non-stationary video sequences based on spatial saliency maps

Favorskaya et al., 2016

Document ID
2246183937092906728
Author
Favorskaya M
Buryachenko V
Publication year
Publication venue
Intelligent Interactive Multimedia Systems and Services 2016

External Links

Snippet

In recent years, a number of methods of salient object detection in images have been proposed in the field of computer vision. However, sometimes the shooting conditions are far from the ideal, and the unpredicted camera jitters significantly impair the quality of video …
Continue reading at link.springer.com (other versions)

Classifications

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    • 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
    • GPHYSICS
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    • G06K9/6267Classification techniques
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    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
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    • G06T2207/10024Color image
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    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
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    • G06K9/00771Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
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    • G06K9/6201Matching; Proximity measures
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    • G06K9/00221Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
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    • 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

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