Pengenalan Gerak Manusia Menggunakan Algoritma Relevance Vector Machine pada MSRC-12 Dataset

Abstract

Relevance vector machine is a popular machine learning technique that is motivated by statistical learning theory. RVM can be used for gesture recognition which is one of the communication tools used by humans. This study proposes an experiment using the Relevance Vector Machine (RVM) algorithm on gesture data from Microsoft Research Cambridge-12 (MSRC-12) as a proposed solution to overcome unbalanced problems in data processing. The results of the study are the accuracy for 1-person motion model reaches 100% and the lowest accuracy with 5 people the motion model reaches 96%. Graphically, the more people or models, the lower the algorithm's accuracy.