Patent ID: 9448636
Filing Date: 2016-09-20
CPC Classification: A63F,G06F,G06K

Claim Text:
1. A method of identifying a gesture of a subject based on self-referential gesture data compressed by principal joint variable analysis in combination with principal component analysis, the method comprising: receiving, by a classifier of a system, a stream of reference frames from a detector unit, the stream of reference frames comprising a set of self-referential gesture data points provided in three dimensions, each self-referential gesture data point identifying locations or positions of one or more parts of a body of a subject with respect to a reference body point on the body of the subject with respect to a particular dimension of the three dimensions; determining, by the classifier, that a subset of the set of self-referential gesture data points is sufficient to recognize a reference gesture; generating, by the classifier, a feature matrix, each row of the feature matrix (i) representative of a particular location or position of the one or more parts of the body, and (ii) having at east three cells, each cell storing a self-referential gesture data point of the set of self-referential gesture data points corresponding to the particular location or position of the one or more parts of the body in one of the three dimensions; transforming the feature matrix into a compressed feature matrix using a principal joint variable analysis function at a pre-defined variance threshold in combination with a principal component analysis function, collapsing the feature matrix by reducing the three-dimensional data set into a two-dimensional data set or a single-dimensional data set, the compressed feature matrix maintaining only the rows of the feature matrix having a corresponding variance greater than the pre-defined variance threshold; storing, into a database of the system, the compressed feature matrix representative of the reference gesture; receiving, by a recognizer of the system, a new stream of frames including new self-referential gesture data points, each new self-referential gesture data point identifying a location of a part of a body of a new subject with respect to the reference body point on the body of the new subject; recognizing, by the recognizer, that the gesture of the new subject corresponds to the reference gesture by comparing only the new self-referential gesture data points corresponding to the self-referential gesture data points in the compressed feature matrix; and determining that the gesture of the new subject corresponds to the reference gesture when the new self-referential gesture data points corresponding to the compressed feature matrix only vary from the data set of the compressed feature matrix within a pre-defined recognition threshold.