Robust 3D Action Recognition Through Sampling Local Appearances and Global Distributions
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DOI: 10.1109/tmm.2017.2786868
Abstract: Three-dimensional (3-D) action recognition has broad applications in human–computer interaction and intelligent surveillance. However, recognizing similar actions remains challenging since previous literature fails to capture motion and shape cues effectively from noisy depth data. In… read more here.
Keywords: based stips; action recognition; motion; shape cues ... See more keywords