Patent ID: 9208376
Filing Date: 2015-12-08
Classification: G06K

Abstract:
1. A method for identifying an unknown person from amongst N known persons, the method comprising: receiving skeleton data of the unknown person from a plurality of skeleton recording devices, wherein the skeleton data comprises data of multiple skeleton joints of the unknown person; extracting, by a processor, G gait feature vectors from the skeleton data of the unknown person; classifying, by the processor, each of the G gait feature vectors into one of N classes based on a training dataset for the N known persons, wherein a class, from the N classes, represents one of the N known persons; computing, by the processor, a classification score for each of the N classes, wherein the classification score for a respective class is a number of gait feature vectors classified in the respective class divided by G; clustering, by the processor, the training dataset for the N known persons into M clusters based on M predefined characteristic attributes of the N known persons, wherein a cluster, from the M clusters, is indicative of known persons with one of the M predefined characteristic attributes; tagging, by the processor, each of the G gait feature vectors with one of the M clusters based on a distance between a respective gait feature vector and cluster centers of the M clusters; determining, a clustering score for each of the M clusters, wherein the clustering score for a respective cluster is a number of gait feature vectors associated with the respective cluster divided by G; and identifying the unknown person, from amongst the N known persons, based on the clustering scores and the classification scores.