Automatic method for Recognition of Colombian Sign Language for vowels and numbers from zero to five by using SVM and KNN
2019 Congreso Internacional de Innovación y Tendencias en Ingenieria (CONIITI )(2019)
摘要
This paper presents a technique for the classification of images and recognition of vowels and numbers from 0 to 5 of Colombian Sign Language (CSL). This work contains six stages: Data set construction, pre-processing, feature extraction, sampling, classification and reporting result. The classification stage is done by using Support Vector Machines (SVM) with Kernel RBF and K-Nearest Neighbor (KNN), after applying cross-validation of 5-folds and the data is divided with different percentages of training set and test set. With the dataset and the sampling of 80%-20% the best results were for SVM with precision performance measures, Recall and F1-Score was obtained 70%, 69%, 69% respectively.
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关键词
Cross validation,Colombian Sign Language (CSL),machine learning,hand gesture recognition,K-Nearest Neighbor (KNN),Support Vector Machine (SVM)
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