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dc.contributor.authorWatchanan Chantapakulen_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.contributor.authorNipon Theera-Umponen_US
dc.contributor.authorNavadon Khunlertgiten_US
dc.description.abstract© 2018 IEEE. Biometrics is a method to identify a person. However, there are several biometric techniques including face recognition, palm recognition, iris recognition, fingerprint recognition, and so on. There is a new approach in biometrics, i.e., identification using full-body movement. In this paper, we introduce a full-body movement in human identification using three Kinects. In particular, we utilize the string grammar fuzzy-possibilistic C-medians (sgFPCMed) to group string sequences from skeleton frames into pose string, then group the pose string sequences of each person into multi-group to create multi-prototypes for each person. The K-nearest neighbor is used to identify the person in the test process on 27 subjects. The system yields 73.33% correct classification on the best validation set of four-fold cross validation.en_US
dc.subjectChemical Engineeringen_US
dc.subjectComputer Scienceen_US
dc.titlePerson identification from full-body movement using string grammar fuzzy-possibilistic C-mediansen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleProceedings - 8th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2018en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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