机器人建模与控制 |
|
|
|
|
基于本体的物品属性类人认知及推理 |
李泚泚, 田国会, 张梦洋, 张营 |
山东大学 控制科学与工程学院, 山东 济南 250061 |
|
Ontology-based humanoid cognition and reasoning of object attributes |
LI Ci-ci, TIAN Guo-hui, ZHANG Meng-yang, ZHANG Ying |
School of Control Science and Engineering, Shandong University, Jinan 250061, China |
引用本文:
李泚泚, 田国会, 张梦洋, 张营. 基于本体的物品属性类人认知及推理[J]. 浙江大学学报(工学版), 2018, 52(7): 1231-1238.
LI Ci-ci, TIAN Guo-hui, ZHANG Meng-yang, ZHANG Ying. Ontology-based humanoid cognition and reasoning of object attributes. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(7): 1231-1238.
链接本文:
http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2018.07.001
或
http://www.zjujournals.com/eng/CN/Y2018/V52/I7/1231
|
[1] 戈尔茨坦.认知心理学-心智、研究与你的生活[M].3版.张明,王佳莹,康静梅,等,译.北京:中国轻工业出版社,2015:315-333.
[2] FARHADI A, ENDRES I, HOIEM D, et al. Describing objects by their attributes[C]//Proceedings of CVPR. Miami:IEEE, 2009:1778-1785.
[3] SUN Y Y, BO L, FOX D. Attribute based object identification[C]//Proceedings of ICRA. Karlsruhe:IEEE, 2013:2096-2103.
[4] ZHU Y, FATHI A, LI F F. Reasoning about object affordances in a knowledge base representation[C]//Proceedings of ECCV. Zurich:Springer, 2014:408-424.
[5] LAMPERT C H, NICKISCH H, HARMELING S. Learning to detect unseen object classes by between-class attribute transfer[C]//Proceedings of CVPR. Miami:IEEE, 2009:951-958.
[6] DUAN D, PARIKH D, CRANDALL D, et al. Discovering localized attributes for fine-grained recognition[C]//Proceedings of CVPR 2012. Providence: IEEE, 2012:3474-3481.
[7] GUPATA A, KEMBHAVI A, DAVIS L S. Observing human-object interactions:using spatial and functional compatibility for recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009,31(10):1775-1789.
[8] RUIKEN D, WONG J M, LIU T Q, et al. Affordance-based active belief:recognition using visual and manual actions[C]//Proceedings of IROS. Daejeon:IEEE, 2016:5312-5317.
[9] KOPPULA H S, GUPTA R, SAXENA A. Learning human activities and object affordances from RGB-D videos[J]. International Journal of Robotics Research, 2013, 32(8):951-970.
[10] KOPPULA H S, GUPTA R, SAXENA A. Anticipating human activities using object affordances for reactive robotic response[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 38(1):14-29.
[11] LINDNER F, ESCHENBACH C. Affordance-based activity placement in human-robot shared environments[C]//Proceedings of ICSR. Bristol:Spring, 2013:94-103.
[12] TENORTH M, BEETZ M. Representations for robot knowledge in the KnowRob framework[J]. Artificial Intelligence, 2015, 247(2017):151-169.
[13] BASILE V, CABRIO E, GANDON F. Building a general knowledge base of physical objects for robots[C]//Proceedings of ESWC. Heraklion:Springer, 2016:8-11.
[14] 阎红灿.本体建模与语义Web知识发现[M].北京:清华大学出版社,2015:145-146.
[15] 安东尼乌.语义网基础教程[M].陈小平,周熠,杨斌,等,译.北京:机械工业出版社,2014:87-89.
[16] SILBERER C, FERRARI V, LAPATA M. Models of semantic representation with visual attributes[C]//2013 ACL Annual Meeting of the Association for Computational Linguistics. Sofia:[s. n.], 2013:572-582.
[17] FELLBAUM C, MILLER G. WordNet:an electronic Lexical database[M]. London:MIT, 1998:71-423.
[18] TENORTH M, PROFANTER S, BALINT-BENCZEDI F, et al. Decomposing CAD models of objects of daily use and reasoning about their functional parts[C]//Proceedings of IROS. Vilamoura:IEEE, 2013:5943-5949.
[19] HERMANS T, REHG J. M, BOBICK A. Affordance prediction via learned object attributes[C]//Proceedings of the ICRA. Portugal:[s. n.], 2011:1-8.
[20] 蒋湛,姚晓明,林兰芬.基于特征自适应的本体映射方法[J].浙江大学学报:工学版,2014,48(1):76-84. JIANG Zhan, YAO Xiao-ming, LIN Lan-fen. Feature-based adaptive method of ontology mapping[J]. Journal of Zhejiang University:Engineering Science, 2014, 48(1):76-84.
[21] HORROCKS I, PATEL-SCHNEIDER P F, BOLEY H, et al. SWRL:a semantic Web rule language combining OWL and RuleML[EB/OL]. (2004-03-21)[2018-01-24]. https://www.w3.org/Submission/SWRL/.
[22] UEDA T, IZUMI N, MORITA Y, et al. Jena-Java framework for developing semantic Web applications[J]. Journal of Japanese Society for Artificial Intelligence, 2004, 19(3):325-333.
[23] MYSQL A. MySQL:the world's most popular open source database[EB/OL].[2018-01-24]. https://www.mysql.com/. |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|