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Wang et al., 2013 - Google Patents

Hand gesture recognition based on fingertip detection

Wang et al., 2013

Document ID
1552383610337039168
Author
Wang M
et al.
Publication year
Publication venue
2013 Fourth Global Congress on Intelligent Systems

External Links

Snippet

To improve the hand gesture recognition accuracy based on Hu moment features, a new recognition algorithm was developed based on the fingertip structure detection. Firstly, the geometric features, the areas of skin region and the image, were designed to segment the …
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Classifications

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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
    • G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
    • G06K9/4609—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections by matching or filtering
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6201—Matching; Proximity measures
    • G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
    • G—PHYSICS
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    • G06K9/00335—Recognising movements or behaviour, e.g. recognition of gestures, dynamic facial expressions; Lip-reading
    • G06K9/00355—Recognition of hand or arm movements, e.g. recognition of deaf sign language
    • G—PHYSICS
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/68—Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
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    • G06K9/62—Methods or arrangements for recognition using electronic means
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    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
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    • G—PHYSICS
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    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00362—Recognising human body or animal bodies, e.g. vehicle occupant, pedestrian; Recognising body parts, e.g. hand
    • G06K9/00375—Recognition of hand or arm, e.g. static hand biometric or posture recognition
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    • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
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    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G—PHYSICS
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    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
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    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/017—Gesture based interaction, e.g. based on a set of recognized hand gestures
    • G—PHYSICS
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    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details

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