TY - GEN
T1 - Unstructured robot perception through Internet semantic concept learning
AU - Wang, Fengchao
AU - Chen, Dongdong
AU - Yuan, Peijiang
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/12/23
Y1 - 2014/12/23
N2 - Intelligent robot is one of the most important ongoing technologies both in industry and social life. Smart perception is the key technology for intelligent robots. Lack of training data, there has been many barriers for intelligent robot to learn the unstructured environment. In this paper, an automatic data mining method for smart robots to learn semantic concepts from videos crawled to known Internet video/image websites (e.g. video-Baidu, Bing, Youku) is presented. An updated novel Internet video-mining method is addressed. An automatic graph model generator is addressed as well as the weight assignment for concepts-relationship learning based on known ontology and an automated video source discovery method in concepts detection from the massive Internet videos is proposed. Experimental results with Tera-bytes level videos show that the method is effective and efficient to solve the smart perception for intelligent robots.
AB - Intelligent robot is one of the most important ongoing technologies both in industry and social life. Smart perception is the key technology for intelligent robots. Lack of training data, there has been many barriers for intelligent robot to learn the unstructured environment. In this paper, an automatic data mining method for smart robots to learn semantic concepts from videos crawled to known Internet video/image websites (e.g. video-Baidu, Bing, Youku) is presented. An updated novel Internet video-mining method is addressed. An automatic graph model generator is addressed as well as the weight assignment for concepts-relationship learning based on known ontology and an automated video source discovery method in concepts detection from the massive Internet videos is proposed. Experimental results with Tera-bytes level videos show that the method is effective and efficient to solve the smart perception for intelligent robots.
KW - Automatic Data Mining
KW - Graphic-Model Generator
KW - Robot perception
KW - Semantic Concept
UR - https://www.scopus.com/pages/publications/84921294755
U2 - 10.1109/MFI.2014.6997683
DO - 10.1109/MFI.2014.6997683
M3 - 会议稿件
AN - SCOPUS:84921294755
T3 - Proceedings of 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, MFI 2014
BT - Proceedings of 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, MFI 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, MFI 2014
Y2 - 28 September 2014 through 30 September 2014
ER -