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We use Latent-Dynamic Conditional Random Fields to perform skeleton-basedpointing gesture classification at each time instance of a video sequence,where we achieve a frame-wise pointing accuracy of roughly 83%. Subsequently,we determine continuous time sequences of arbitrary length that form individualpointing gestures and this way reliably detect pointing gestures at a falsepositive detection rate of 0.63%.

What's the point? Frame-wise Pointing Gesture Recognition with Latent-Dynamic Conditional Random Fields