Classification of facial part movement acquired from Kinect V1 and Kinect V2
The aim of this study is to determine the motion sensor with better performance in facial part movements recognition among Kinect v1 and Kinect v2. This study has applied some classification methods such as neural network, complex decision tree, cubic SVM, fine Gaussian SVM, fine kNN and QDA in the...
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| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Springer
2021
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/33563/1/Classification%20of%20facial%20part%20movement%20acquired%20from%20Kinect%20V1%20.pdf http://umpir.ump.edu.my/id/eprint/33563/2/Classification%20of%20facial%20part%20movement%20acquired%20from%20Kinect%20V1_FULL.pdf http://umpir.ump.edu.my/id/eprint/33563/ https://doi.org/10.1007/978-981-15-5281-6_65 |
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