Identifying gestures using gesture data compressed by PCA, principal joint variable analysis, and compressed feature matrices

摘要

Systems and method described herein present techniques for identifying a gesture using gesture data compressed by principal joint variable analysis. A classifier of a gesture recognition system may receive a frame comprising a set of gesture data points identifying locations of body parts of a subject. The classifier may determining that a subset of the set of gesture data points is sufficient to recognize a first gesture. The subset may be stored into a database in reference to the first gesture. A recognizer may receive a new frame of new gesture data points identifying locations of body parts of a new subject. The recognizer may recognize that the gesture of the new subject corresponds to the first gesture responsive to comparing at least one new gesture data point from the new frame to at least one gesture data point of the subset.