Study on Hand Gesture Recognition and Portfolio Optimization Model Based on SVM

Abstract

Abstract: Hand gesture recognition was researched. The idea of extracting related features was proposed by using SVM algorithm in machine learning domain, and combination optimization method was used, which consists of ANN, HMM and DTW, to do hand gesture recognition. The experimental results show that portfolio optimization model based gesture recognition method has high accuracy and is very effective.

Key words: gesture recognition, support vector machine, combinatorial optimization, feature extraction, virtual reality

CLC Number:

TP391.41

Cai Zhiwei, Wu Shuyan, Song Junfeng. Study on Hand Gesture Recognition and Portfolio Optimization Model Based on SVM[J]. Journal of System Simulation, 2016, 28(8): 1812-1817.

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