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Hand gesture recognition using K-means clustering and Support Vector Machine
Maharani D.A.a, Fakhrurroja H.a, Riyantoa, Machbub C.a
a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018 IEEE.Human-Robot Interaction (HRI) requires media for communication which can be both understood by robot and easily done by human. Usually, human using oral language to communicate but there are some situations that require performing non-verbal activities such as deaf people, patient, and old people, therefore gesture recognition as communication media is needed to give order to Robot. This paper discusses hand gesture recognition as input command for Bioloid Premium Robot using two methods, K-Means clustering and Support Vector Machine (SVM) with directed acyclic graph (DAG) decision. Four gestures (forward, right, left and stop) were recognized using Kinect v2. The testing was done 6 peoples for three distances (2m, 3m, and 4m) and three slopes position (45, 0,-45). The SVM required 10ms recognition time with accuracy reached 95.15%, while K-Means needed 4.45ms recognition time with 77.42% accuracy. This study resulted in Multiclass SVM with DAG decision performs better than K-Means clustering method.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]BIOLOID,Communication media,Directed acyclic graph (DAG),Hand-gesture recognition,Human robot Interaction (HRI),K – means clustering,K-means clustering method,Kinect v2[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Bioloid Premium Robot,K-Means Clustering,Kinect v2,Support Vector Machine (SVM)[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]ACKNOWLEDGMENT This work was supported by Program of Post Graduate Team Research 2017 (Penelitian Tim Pasca Sarjana 2017) from The Ministry of Research, Technology and Higher Education, Republic of Indonesia.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ISCAIE.2018.8405435[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]