Tangkuampien et al., 2006 - Google Patents

Real-Time Human Pose Inference using Kernel Principal Component Pre-image Approximations.

Tangkuampien et al., 2006

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Document ID
188229282114375128
Author
Tangkuampien T
Suter D
Publication year
Publication venue
BMVC

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Snippet

We present a real-time markerless human motion capture technique based on un-calibrated synchronized cameras. Training sets of real motions captured from marker based systems are used to learn an optimal pose manifold of human motion via Kernel Principal …
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Classifications

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    • G06K9/6201—Matching; Proximity measures
    • G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
    • G06K9/6203—Shifting or otherwise transforming the patterns to accommodate for positional errors
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    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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