Classification Algorithm for Person Identification and Gesture Recognition Based on Hand Gestures with Small Training Sets.

ABSTRACT: Classification algorithms require training data initially labelled by classes to build a model and then to be able to classify the new data. The amount and diversity of training data affect the classification quality and usually the larger the training set, the better the accuracy of classification. In many applications only small amounts of training data are available. This article presents a new time series classification algorithm for problems with small training sets. The algorithm was tested on hand gesture recordings in tasks of person identification and gesture recognition. The algorithm provides significantly better classification accuracy than other machine learning algorithms. For 22 different hand gestures performed by 10 people and the training set size equal to 5 gesture execu

SUBMITTER: Rzecki K 

PROVIDER: S-EPMC7766068 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature