On Pose Estimation for Human-Robot Symbiosis
This paper presents a vision based pose estimation system using knowledge based approach for humanrobot symbiosis. The system is based on visual information of the face by connected component analysis of the skin color segmentation of images in HSV color model and is commenced with the face recognit...
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| Published in: | International Journal of Advanced Robotic Systems Vol. 5; no. 1 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English Japanese |
| Published: |
SAGE Publications
01.01.2008
SAGE Publishing |
| Subjects: | |
| ISSN: | 1729-8806, 1729-8814 |
| Online Access: | Get full text |
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| Abstract | This paper presents a vision based pose estimation system using knowledge based approach for humanrobot symbiosis. The system is based on visual information of the face by connected component analysis of the skin color segmentation of images in HSV color model and is commenced with the face recognition and pose classification scheme using subspace PCA based pattern-matching strategies. With the knowledge of the known user's profile, face poses are then classified by multilayer perceptron. Based on the frame-based knowledge representation approach, face poses are being interpreted using the Software Platform for Agent and Knowledge (SPAK) management. On face pose recognition, robot is then instructed to perform some specific tasks by issuing pose commands. Experimental results demonstrate that the subspace method is better than that of the standard PCA method for face pose classification. The system has been demonstrated with the implementation of the algorithm to interact with an entertainment robot named, AIBO for human-robot symbiotic relationship. |
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| AbstractList | This paper presents a vision based pose estimation system using knowledge based approach for humanrobot symbiosis. The system is based on visual information of the face by connected component analysis of the skin color segmentation of images in HSV color model and is commenced with the face recognition and pose classification scheme using subspace PCA based pattern-matching strategies. With the knowledge of the known user's profile, face poses are then classified by multilayer perceptron. Based on the frame-based knowledge representation approach, face poses are being interpreted using the Software Platform for Agent and Knowledge (SPAK) management. On face pose recognition, robot is then instructed to perform some specific tasks by issuing pose commands. Experimental results demonstrate that the subspace method is better than that of the standard PCA method for face pose classification. The system has been demonstrated with the implementation of the algorithm to interact with an entertainment robot named, AIBO for human-robot symbiotic relationship. |
| Author | Chang Hong Liu Hideki Ueno Md. Al-Amin Bhuiyan |
| Author_xml | – sequence: 1 orcidid: 0000-0002-7207-6464 fullname: Md. Al-Amin Bhuiyan – sequence: 2 fullname: Chang Hong Liu – sequence: 3 fullname: Hideki Ueno |
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| DOI | 10.60692/4ebtd-axp09 10.5772/5663 10.60692/64w09-ta232 |
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| Snippet | This paper presents a vision based pose estimation system using knowledge based approach for humanrobot symbiosis. The system is based on visual information of... |
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| SubjectTerms | AIBO Artificial intelligence Computer science Computer vision Computer Vision and Pattern Recognition Continuous Recognition Electronic computers. Computer science Electronics Face (sociological concept) Face Recognition Face Recognition and Dimensionality Reduction Techniques Facial recognition system Feature Matching FOS: Sociology Frame (networking) Gesture Recognition Gesture Recognition in Human-Computer Interaction HSV color model Human-Computer Interaction Human-robot symbiosis Image Feature Retrieval and Recognition Techniques Pattern recognition (psychology) PCA Physical Sciences Pose QA75.5-76.95 Robot Segmentation Social science Sociology Subspace topology Telecommunications TK7800-8360 |
| Title | On Pose Estimation for Human-Robot Symbiosis |
| URI | https://cir.nii.ac.jp/crid/1872272492445168384 https://doaj.org/article/6e04c580852b42b8827f883427920ef7 |
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