W. S. M. Sanjaya, D. Anggraeni, Kiki Zakaria, Atip Juwardi, M. Munawwaroh
{"title":"The design of face recognition and tracking for human-robot interaction","authors":"W. S. M. Sanjaya, D. Anggraeni, Kiki Zakaria, Atip Juwardi, M. Munawwaroh","doi":"10.1109/ICITISEE.2017.8285519","DOIUrl":null,"url":null,"abstract":"This paper discusses the development of Social Robot named SyPEHUL (System of Physic, Electronic, Humanoid Robot and Machine Learning) which can recognize and tracking human face. Face recognition and tracking process use Cascade Classification and LBPH (Local Binary Pattern Histogram) Face Recognizer method based on OpenCV library and Python 2.7. The social robot hardware based on Arduino microcontroller contains by 12 DoF (Degree of Freedom) motor servos to actuate robotic head and its face. The face recognition system has been implemented to Social Robot which can recognize and tracking human face and then mentioned the person name. The face recognition system of Social Robot result shows a good accuracy for Human-Robot Interaction.","PeriodicalId":130873,"journal":{"name":"2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"235 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITISEE.2017.8285519","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
This paper discusses the development of Social Robot named SyPEHUL (System of Physic, Electronic, Humanoid Robot and Machine Learning) which can recognize and tracking human face. Face recognition and tracking process use Cascade Classification and LBPH (Local Binary Pattern Histogram) Face Recognizer method based on OpenCV library and Python 2.7. The social robot hardware based on Arduino microcontroller contains by 12 DoF (Degree of Freedom) motor servos to actuate robotic head and its face. The face recognition system has been implemented to Social Robot which can recognize and tracking human face and then mentioned the person name. The face recognition system of Social Robot result shows a good accuracy for Human-Robot Interaction.