More Web Proxy on the site http://driver.im/

research-article

Open access

A survey on ontologies for human behavior recognition

Authors:

Natalia Díaz Rodríguez,

M. P. Cuéllar,

Miguel Delgado Calvo-FloresAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 46, Issue 4

Article No.: 43, Pages 1 - 33

https://doi.org/10.1145/2523819

Published: 01 March 2014 Publication History

Abstract

Describing user activity plays an essential role in ambient intelligence. In this work, we review different methods for human activity recognition, classified as data-driven and knowledge-based techniques. We focus on context ontologies whose ultimate goal is the tracking of human behavior. After studying upper and domain ontologies, both useful for human activity representation and inference, we establish an evaluation criterion to assess the suitability of the different candidate ontologies for this purpose. As a result, any missing features, which are relevant for modeling daily human behaviors, are identified as future challenges.

References

[1]

Bessam Abdualrazak, Yasir Malik, and Hen-I Yang. 2010. A taxonomy driven approach towards evaluating pervasive computing system. In Proceedings of the Aging Friendly Technology for Health and Independence, and 8th International Conference on Smart Homes and Health Telematics (ICOST’10). Springer-Verlag, Berlin, 32--42.

Digital Library

[2]

G. Acampora and V. Loia. 2005. Fuzzy control interoperability and scalability for adaptive domotic framework. IEEE Transactions on Industrial Informatics 1, 2 (2005), 97--111.

[3]

J. K. Aggarwal and M. S. Ryoo. 2011. Human activity analysis: A review. ACM Computing Surveys. 43, 3, Article 16 (April 2011), 43 pages.

Digital Library

[4]

Alessandra Agostini, Claudio Bettini, and Daniele Riboni. 2009. Hybrid reasoning in the CARE middleware for context awareness. International Journal of Web Engineering and Technology 5, 1 (2009), 3--23.

Digital Library

[5]

M. Amoretti, F. Wientapper, F. Furfari, S. Lenzi, and S. Chessa. 2010. Sensor data fusion for activity monitoring in ambient assisted living environments. In Sensor Systems and Software, Stephen Hailes, Sabrina Sicari, and George Roussos (Eds.). Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Vol. 24. Springer, Berlin, 206--221.

[6]

Francisco Arce, José Mario, and García Valdez. 2010. Accelerometer-based hand gesture recognition using artificial neural networks. Soft Computing 318 (2010), 67--77.

[7]

J. Augusto. 2007. Ambient intelligence: The confluence of pervasive computing and artificial intelligence. In Intelligent Computing Everywhere, A. Schuster (Ed.). Springer, Berlin, 213--234.

[8]

Matthias Baldauf, Schahram Dustdar, and Florian Rosenberg. 2007. A survey on context-aware systems. International Journal of Ad Hoc and Ubiquitous Computing 2, 4, 263--277.

Digital Library

[9]

N. Baumgartner and W. Retschitzegger. 2006. A survey of upper ontologies for situation awareness. In Proceedings of the 4th IASTED International Conference on Knowledge Sharing and Collaborative Engineering. 1--9.

[10]

Claudio Bettini, Linda Pareschi, and Daniele Riboni. 2008. Efficient profile aggregation and policy evaluation in a middleware for adaptive mobile applications. Pervasive and Mobile Computing 4, 5 (2008), 697--718.

Digital Library

[11]

Fernando Bobillo and Umberto Straccia. 2011. Fuzzy ontology representation using OWL 2. International Journal of Approximate Reasoning 52, 7 (2011), 1073--1094.

Digital Library

[12]

J. Boger, J. Hoey, P. Poupart, C. Boutilier, G. Fernie, and A. Mihailidis. 2006. A planning system based on Markov decision processes to guide people with dementia through activities of daily living. IEEE Transactions on Information Technology in Biomedicine 10, 2, 323--333.

Digital Library

[13]

Willem Nico Borst. 1997. Construction of Engineering Ontologies for Knowledge Sharing and Reuse. Ph.D. Dissertation. Institute for Telematica and Information Technology, University of Twente, Enschede, The Netherlands.

[14]

O. Brdiczka, P. Reignier, and J. Crowley. 2007. Detecting individual activities from video in a smart home. In Proceedings of the International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. 363--370.

Digital Library

[15]

A. J. Brush, J. Scott, and J. Krumm. 2010. Activity recognition research: The good, the bad, and the future. In Proceedings of the 2010 Pervasive Workshop.

[16]

J. M. Cantera-Fonseca and R. Lewis. 2009. Delivery context ontology. W3C Working Draft.

[17]

Roberto Casas, Rubén Blasco Marín, Alexia Robinet, Armando Roy Delgado, Armando Roy Yarza, John Mcginn, Richard Picking, and Vic Grout. 2008. User modelling in ambient intelligence for elderly and disabled people. In Proceedings of the 11th International Conference on Computers Helping People with Special Needs (ICCHP’08). Springer-Verlag, Berlin, 114--122.

Digital Library

[18]

Alexandros André Chaaraoui, Pau Climent-Pérez, and Francisco Flórez-Revuelta. 2012. A review on vision techniques applied to human behaviour analysis for ambient-assisted living. Expert Syst. Appl. 39, 12 (2012), 10873--10888.

Digital Library

[19]

Harry Chen, Tim Finin, and Anupam Joshi. 2003. An ontology for context-aware pervasive computing environments. In Proceedings of the Workshop on Ontologies in Agent Systems.

Digital Library

[20]

Harry Chen, Tim Finin, and Anupam Joshi. 2005. The SOUPA ontology for pervasive computing. In Ontologies for Agents: Theory and Experiences, Valentina Tamma, Stephen Cranefield, Timothy W. Finin, and Steven Willmott (Eds.). Birkhäuser Basel, 233--258.

[21]

Liming Chen, Chris Nugent, Maurice Mulvenna, Dewar Finlay, Xin Hong, and Michael Poland. 2008. Using event calculus for behaviour reasoning and assistance in a smart home. In Smart Homes and Health Telematics, Sumi Helal, Simanta Mitra, Johnny Wong, CarlK. Chang, and Mounir Mokhtari (Eds.). Lecture Notes in Computer Science, Vol. 5120. Springer, Berlin, 81--89.

Digital Library

[22]

Liming Chen and Chris D. Nugent. 2009. Ontology-based activity recognition in intelligent pervasive environments. International Journal of Web Information Systems (IJWIS) 5, 4 (2009), 410--430.

[23]

Liming Chen, George Okeyo, Hui Wang, Roy Sterritt, and Chris D. Nugent. 2011. A systematic approach to adaptive activity modeling and discovery in smart homes. In Proceedings of the 4th International Conference on Biomedical Engineering and Informatics (BMEI). 2192--2196.

[24]

Luke L. Chen and Jit Biswas. 2009. Tutorial: an introduction to ontology-based activity recognition. In Proceedings of the 7th International Conference on Mobile Computing and Multimedia (MoMM’09).

Digital Library

[25]

Wongun Choi, C. Pantofaru, and S. Savarese. 2011. Detecting and tracking people using an RGB-D camera via multiple detector fusion. In Proceedings of the 2011 IEEE International Conference on Computer Vision Workshops. 1076--1083.

[26]

Diane J. Cook, Juan C. Augusto, and Vikramaditya R. Jakkula. 2009. Review: Ambient intelligence: Technologies, applications, and opportunities. Pervasive Mobile Computing 5, 4 (2009), 277--298.

Digital Library

[27]

Diane J. Cook and Sajal K. Das. 2005. Smart Environments: Technology, Protocols and Applications. John Wiley.

Digital Library

[28]

Aaron Crandall and Diane J. Cook. 2010. Learning activity models for multiple agents in a smart space. In Handbook of Ambient Intelligence and Smart Environments, Hideyuki Nakashima, Hamid Aghajan, and JuanCarlos Augusto (Eds.). Springer, New York, 751--769.

[29]

Miguel Delgado, Maria Ros, and Amparo Vila. 2009. Correct behavior identification system in a tagged world. Expert Systems with Applications 36, 6 (2009), 9899--9906.

Digital Library

[30]

Anind K. Dey and Gregory D. Abowd. 2000. The Context Toolkit: Aiding the development of context-aware applications. In Proceedings of the Workshop on Software Engineering for Wearable and PervasiveComputing.

[31]

F. Doctor, H. Hagras, and V. Callaghan. 2005. A fuzzy embedded agent-based approach for realizing ambient intelligence in intelligent inhabited environments. IEEE Trans. Syst. Man Cybernet. Part A 35, 1 (2005), 55--65.

Digital Library

[32]

K. Ducatel, M. Bogdanowicz, F. Scapolo, J. Leijten, and J.-C. Burgelman. 2001. Scenarios for Ambient Intelligence in 2010. European Commission Community Research.

[33]

Saibal Dutta, Amitava Chatterjee, and Sugata Munshi. 2009. An automated hierarchical gait pattern identification tool employing cross-correlation-based feature extraction and recurrent neural network based classification. Expert Systems 26, 2 (2009), 202--217.

[34]

Dejene Ejigu, Marian Scuturici, and Lionel Brunie. 2007. An ontology-based approach to context modeling and reasoning in pervasive computing. In Proceedings of the 5th Annual IEEE International Conference on Pervasive Computing and Communications. Workshops. 14--19.

Digital Library

[35]

M. Ermes, J. Parkka, J. Mantyjarvi, and I. Korhonen. 2008. Detection of daily activities and sports with wearable sensors in controlled and uncontrolled conditions. IEEE Transactions on Information Technology in Biomedicine 12, 1 (2008), 20--26.

Digital Library

[36]

Asma Gharsellaoui, Yacine Bellik, and Christophe Jacquet. 2012. Requirements of task modeling in ambient intelligent environments. In Proceedings of the 2nd International Conference on Ambient Computing, Applications, Services and Technologies. IARIA, 71--78.

[37]

Tao Gu, Hung Keng Pung, and Da Qing Zhang. 2004. A middleware for building context-aware mobile services. In Proceedings of IEEE Vehicular Technology Conference.

[38]

Tao Gu, Zhanqing Wu, Xianping Tao, Hung Keng Pung, and Jian Lu. 2009. epSICAR: An emerging patterns based approach to sequential, interleaved and concurrent activity recognition. In Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications (PerCom’09). IEEE Computer Society, Washington, DC, 1--9.

Digital Library

[39]

Juan Gómez-Romero, Miguel A. Patricio, Jesús García, and José M. Molina. 2011. Ontology-based context representation and reasoning for object tracking and scene interpretation in video. Expert Systems with Applications 38, 6 (2011), 7494--7510.

Digital Library

[40]

H. Hagras, V. Callaghan, M. Colley, G. Clarke, A. Pounds-Cornish, and H. Duman. 2004. Creating an ambient-intelligence environment using embedded agents. IEEE Intelligent Systems 19, 6 (2004), 12--20.

Digital Library

[41]

Ramón Hervás, José Bravo, and Jesús Fontecha. 2010. A context model based on ontological languages: A proposal for information visualization. Journal of Universal Computer Science 16, 12 (2010), 1539--1555.

[42]

Xin Hong, Chris Nugent, Maurice Mulvenna, Sally McClean, Bryan Scotney, and Steven Devlin. 2009. Evidential fusion of sensor data for activity recognition in smart homes. Pervasive and Mobile Computing 5, 3 (2009), 236--252.

Digital Library

[43]

V. Jakkula, A. Crandall, and D. J. Cook. 2007. Knowledge discovery in entity-based smart environment resident data using temporal relations-based data mining. In Proceedings of the ICDM Workshop on Spatial and Spatio-Temporal Data Mining. 531--579.

Digital Library

[44]

Julie A. Kientz, Shwetak N. Patel, Brian Jones, Ed Price, Elizabeth D. Mynatt, and Gregory D. Abowd. 2008. The Georgia Tech aware home. In CHI’08 Extended Abstracts on Human Factors in Computing Systems. ACM, New York, NY, 3675--3680.

Digital Library

[45]

Eunju Kim, Sumi Helal, and D. Cook. 2010. Human activity recognition and pattern discovery. IEEE Pervasive Computing 9, 1 (2010), 48--53.

Digital Library

[46]

G. Klyne, F. Reynolds, C. Woodrow, H. Ohto, J. Hjelm, M. H. Butler, and L. Tran. 2004. Composite Capability/Preference Profiles (CC/PP): Structure and Vocabularies 1.0. W3C Recommendation. Retrieved from http://www.w3.org/TR/CCPP-struct-vocab/.

[47]

Laszlo Kovacs, Peter Matetelki, and Balazs Pataki. 2009. Service-oriented context-aware framework. In Proceedings of the Young Researchers Workshop on Service-Oriented Computing.

[48]

R. Kowalski and M. Sergot. 1986. A logic-based calculus of events. New Generation Computing 4, 1 (1986), 67--95.

Digital Library

[49]

Chin-Feng Lai, Yueh-Min Huang, Jong Hyuk Park, and Han-Chieh Chao. 2010. Adaptive body posture analysis for elderly-falling detection with multisensors. IEEE Intelligent Systems 25, 2 (2010), 20--30.

Digital Library

[50]

Hector J. Levesque, Fiora Pirri, and Ray Reiter. 1998. Foundations for the situation calculus. Electronic Transactions on Artificial Intelligence 2 (1998), 159--178.

[51]

Fei Li and Schahram Dustdar. 2011. Incorporating unsupervised learning in activity recognition. In Activity Context Representation (AAAI Workshops), Vol. WS-11-04. AAAI.

[52]

Jiayang Liu, Zhen Wang, Lin Zhong, J. Wickramasuriya, and V. Vasudevan. 2009. uWave: Accelerometer-based personalized gesture recognition and its applications. In Proceedings of the IEEE International Conference on Pervasive Computing and Communications (PerCom’09). 1--9.

Digital Library

[53]

Zongyi Liu and Sudeep Sarkar. 2006. Improved gait recognition by gait dynamics normalization. IEEE Transactions on Pattern Analysis and Machine Intelligence 28 (2006), 2006.

Digital Library

[54]

A Lozano-Tello and A Gómez-Pérez. 2004. ONTOMETRIC: A method to choose the appropriate ontology. Journal of Database Management 15, 2 (2004), 1--18.

[55]

P. López-Matencio, J. Vales Alonso, F. J. González-Castaño, J. L. Sieiro, and J. J. Alcaraz. 2010. Ambient intelligence assistant for running sports based on k-NN classifiers. In Proceedings of the 3rd Conference on Human System Interactions (HSI’10). 605--611.

[56]

Christopher J. Matheus, Mieczyslaw M. Kokar, Kenneth Baclawski, Jerzy Letkowski, Catherine Call, Michael Hinman, John Salerno, and Douglas Boulware. 2005. SAWA: An assistant for higher-level fusion and situation awareness. In Proceedings of the 8th International Conference on Information Fusion.

[57]

U. Maurer, A. Smailagic, D. P. Siewiorek, and M. Deisher. 2006. Activity recognition and monitoring using multiple sensors on different body positions. In Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks (BSN’06). 4pp.--116.

Digital Library

[58]

Xiaoning Meng, Ka Keung Lee, and Yangsheng Xu. 2006. Human Driving Behavior Recognition Based on Hidden Markov Models. In Proceedings of the 2006 IEEE International Conference on Robotics and Biomimetics (ROBIO’06). 274--279.

[59]

J. B. Mocholí, P. Sala, C. Fernández-Llatas, and J. C. Naranjo. 2010. Ontology for modeling interaction in ambient assisted living environments. In Proceedings of the XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010, Panagiotis D. Bamidis, Nicolas Pallikarakis, and Ratko Magjarevic (Eds.). IFMBE Proceedings, Vol. 29. Springer, Berlin, 655--658. 10.1007/978-3-642-13039-7_165.

[60]

D. Morris, B. Schazmann, Yangzhe Wu, S. Coyle, S. Brady, J. Hayes, C. Slater, C. Fay, King Tong Lau, G. Wallace, and D. Diamond. 2008. Wearable sensors for monitoring sports performance and training. In Proceedings of the 5th International Summer School and Symposium on Medical Devices and Biosensors (ISSS-MDBS’08). 121--124.

[61]

U. Naeem and J. Bigham. 2007. A comparison of two hidden Markov approaches to task identification in the home environment. In Proceedings of the 2nd International Conference on Pervasive Computing and Applications (ICPCA’07). 383--388.

[62]

Usman Naeem, John Bigham, and Jinfu Wang. 2007. Recognising activities of daily life using hierarchical plans. In Proceedings of the 2nd European Conference on Smart Sensing and Context (EuroSSC’07). Springer-Verlag, Berlin, 175--189.

Digital Library

[63]

B.A. Nardi. 1996. Context and Consciousness: Activity Theory and Human-Computer Interaction. MIT Press.

Digital Library

[64]

George Okeyo, Liming Chen, Hui Wang, and Roy Sterritt. 2010. Ontology-enabled activity learning and model evolution in smart homes. In Ubiquitous Intelligence and Computing, Zhiwen Yu, Ramiro Liscano, Guanling Chen, Daqing Zhang, and Xingshe Zhou (Eds.). Lecture Notes in Computer Science, Vol. 6406. Springer, Berlin, 67--82. 10.1007/978-3-642-16355-5_8.

Digital Library

[65]

R. Oppermann and M. Specht. 2000. A Context-Sensitive Nomadic Exhibition Guide. In Proceedings of the 2nd Symposium on Handheld and Ubiquitous Computing. Springer, 127--142.

Digital Library

[66]

Ronald Poppe. 2010. A survey on vision-based human action recognition. Image and Vision Computing 28, 6 (June 2010), 976--990.

Digital Library

[67]

María Poveda-Villalón, MariCarmen Suárez-Figueroa, and Asunción Gómez-Pérez. 2012. Validating ontologies with OOPS&excl; In Knowledge Engineering and Knowledge Management, Annette Teije, Johanna Völker, Siegfried Handschuh, Heiner Stuckenschmidt, Mathieu d’Acquin, Andriy Nikolov, Nathalie Aussenac-Gilles, and Nathalie Hernandez (Eds.). Lecture Notes in Computer Science, Vol. 7603. Springer, Berlin, 267--281.

Digital Library

[68]

Davy Preuveneers, Jan Van Den Bergh, Dennis Wagelaar, Andy Georges, Peter Rigole, Tim Clerckx, E. Berbers, Karin Coninx, and Koen De Bosschere. 2004. Towards an extensible context ontology for ambient intelligence. In Proceedings of the 2nd European Symposium on Ambient Intelligence. Springer-Verlag, 148--159.

[69]

W. Prinz. 1999. NESSIE: An awareness environment for cooperative settings. In Proceedings of 6th Conference on Computer-Supported Cooperative Work.

Digital Library

[70]

Carlos Ramos, Juan Carlos Augusto, and Daniel Shapiro. 2008. Ambient intelligence—the next step for artificial intelligence. IEEE Intelligent Systems 23, 2 (2008), 15--18.

Digital Library

[71]

P. Rashidi and D. J. Cook. 2009. Keeping the resident in the loop: Adapting the smart home to the user. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans 39, 5 (2009), 949--959.

Digital Library

[72]

P. Rashidi and D. Cook. 2010. Multi home transfer learning for resident activity discovery and recognition. In Proceedings of the International Workshop on Knowledge Discovery from Sensor Data.

[73]

Stefan Reifinger, Frank Wallhoff, Markus Ablassmeier, Tony Poitschke, and Gerhard Rigoll. 2007. Static and dynamic hand-gesture recognition for augmented reality applications. In Proceedings of the 12th International Conference on Human-Computer Interaction: Intelligent Multimodal Interaction Environments (HCI’07). Springer-Verlag, Berlin, 728--737.

Digital Library

[74]

P. Remagnino, H. Hagras, N. Monekosso, and S. Velastin. 2005. Ambient intelligence. In Ambient Intelligence, Paolo Remagnino, Gian Foresti, and Tim Ellis (Eds.). Springer, New York, 1--14.

[75]

Daniele Riboni and Claudio Bettini. 2011a. COSAR: Hybrid reasoning for context-aware activity recognition. Personal and Ubiquitous Computing 15, 3 (2011), 271--289.

Digital Library

[76]

Daniele Riboni and Claudio Bettini. 2011b. OWL 2 modeling and reasoning with complex human activities. Pervasive Mobile Computing 7, 3 (2011), 379--395.

Digital Library

[77]

Daniele Riboni, Linda Pareschi, Laura Radaelli, and Claudio Bettini. 2011. Is ontology-based activity recognition really effective&quest; In PerCom Workshops. 427--431.

[78]

M. Roman, C. Hess, R. Cerqueira, and A. Ranganathan. 2002. A middleware infrastructure for active spaces. In IEEE Pervasive Computing.

Digital Library

[79]

M. Ros, M. P. Cuéllar, M. Delgado, and A. Vila. 2013. Online recognition of human activities and adaptation to habit changes by means of learning automata and fuzzy temporal windows. Information Sciences 220, 20 (2013), 86--101.

Digital Library

[80]

Matthew Rowe, Miriam Fernandez, Sofia Angeletou, and Harith Alani. 2013. Community analysis through semantic rules and role composition derivation. Web Semantics: Science, Services and Agents on the World Wide Web 18, 1 (2013). Retrieved from http://www.websemanticsjournal.org/index.php/ps/article/view/293.

Digital Library

[81]

Nirmalya Roy, Abhishek Roy, and Sajal K. Das. 2006. Context-aware resource management in multi-inhabitant smart homes: A Nash H-learning based approach. In Proceedings of the 4th Annual IEEE International Conference on Pervasive Computing and Communications (PERCOM’06). IEEE Computer Society, Washington, DC, 148--158.

Digital Library

[82]

Mohsin Saleemi, Natalia Díaz Rodríguez, Johan Lilius, and Ivan Porres. 2011. A framework for context-aware applications for smart spaces. In Proceedings of the 4th Conference on Smart Spaces, (ruSMART’11), Sergey Balandin, Yevgeni Koucheryavi, and Honglin Hu (Eds.). LNCS, St. Petersburg, 14--25. Retrieved from http://www.springerlink.com/content/d8618k217710th32/.

Digital Library

[83]

Salim K. Semy, Mary K. Pulvermacher, Leo J. Obrst, and Mary K. Pulvermacher. 2004. Toward the Use of an Upper Ontology for U.S. Government and U.S. Military Domains: An Evaluation. Technical Report. Workshop on Information Integration on the Web (IIWeb-04), in conjunction with VLDB-2004.

[84]

Patrice Seyed. 2012. A method for evaluating ontologies—introducing the BFO-rigidity decision tree wizard. In Proceedings of the 7th International Conference on Formal Ontology in Information Systems (FOIS’12). 191--204.

[85]

Geetika Singla, Diane J. Cook, and Maureen Schmitter-Edgecombe. 2010. Recognizing independent and joint activities among multiple residents in smart environments. Journal of Ambient Intelligence and Humanized Computing 1, 1 (2010), 57--63.

[86]

Markus Stengel. 2003. Introduction to Graphical Models, Hidden Markov Models and Bayesian Networks. Tutorial, Toyohashi University of Technology, Japan.

[87]

Sakari Stenudd. 2012. A model for using machine learning in smart environments. In Proceedings of the 6th International Conference on Grid and Pervasive Computing (GPC’11). Springer-Verlag, Berlin, 24--33.

Digital Library

[88]

Ljiljana Stojanovic. 2004. Methods and Tools for Ontology Evolution. Ph.D. Dissertation. Karlsruhe Institute of Technology. Retrieved from http://digbib.ubka.uni-karlsruhe.de/volltexte/1000003270.

[89]

Thomas Strang and Claudia Linnhoff-Popien. 2004. A context modeling survey. In Proceedings of the Workshop on Advanced Context Modelling, Reasoning and Management, UbiComp 2004 - the 6th International Conference on Ubiquitous Computing.

[90]

T. Strang, C. Linnhoff-Popien, and K. Frank. Nov 2003. CoOL: A context ontology language to enable contextual interoperability. In Proceedings of the 4th International Conference on Distributed Applications and Interoperable Systems. IEEE Computer Society, 236--247.

[91]

E. Tapia, S. Intille, and K. Larson. 2004. Activity recognition in the home using simple and ubiquitous sensors. Pervasive Computing 3001 (2004), 158--175.

[92]

Shoji Tominaga, Masamichi Shimosaka, Rui Fukui, and Tomomasa Sato. 2012. A unified framework for modeling and predicting going-out behavior. In Pervasive Computing, Judy Kay, Paul Lukowicz, Hideyuki Tokuda, Patrick Olivier, and Antonio Krüger (Eds.). Lecture Notes in Computer Science, Vol. 7319. Springer, Berlin, 73--90. 10.1007/978-3-642-31205-2_5.

Digital Library

[93]

Douglas L. Vail, Manuela M. Veloso, and John D. Lafferty. 2007. Conditional random fields for activity recognition. In Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS’07). ACM, New York, NY.

Digital Library

[94]

T. van Kasteren and B. Krose. 2007. Bayesian activity recognition in residence for elders. IET Conference Publications 2007, CP531 (2007), 209--212.

[95]

M. J. van Sinderen, A. T. van Halteren, M. Wegdam, H. B. Meeuwissen, and E. H. Eertink. 2006. Supporting context-aware mobile applications: an infrastructure approach. IEEE Communications Magazine 44, 9 (Sept. 2006), 96--104.

Digital Library

[96]

Maria Poveda Villalon, Mari Carmen Suárez-Figueroa, R. García-Castro, and A. Gómez-Pérez. 2010. A context ontology for mobile environments. In Proceedings of Workshop on Context, Information and Ontologies—CIAO 2010 Co-located with EKAW 2010, Vol. 626. CEUR-WS, Germany.

[97]

J. Vivaldi, J. Feliu, and M. T. Cabré. 2002. Ontologies: A Review, Technical Report eport IULA/INF034/02, University Pompeu Fabra, Institute for Applied Linguistics, Barcelona, Spain.

[98]

Denny Vrandečić. 2010. Ontology Evaluation. Ph.D. Dissertation. KIT Karlsruhe Institute of Technology, Karlsruhe, Germany.

[99]

D. H. Wilson, D. Wyaat, and M. Philipose. 2005. Using context history for data collection in the home. In Proceedings of the 3rd International Conference on Pervasive Computing (PERVASIVE), Vol. 3468.

[100]

Terry Winograd. 2001. Architectures for context. Human Computer Interaction 16, 2 (2001), 401--419.

Digital Library

[101]

Yunfeng Wu and S. Krishnan. 2010. Statistical analysis of gait rhythm in patients with Parkinson’s disease. IEEE Transactions on Neural Systems and Rehabilitation Engineering 18, 2 (2010), 150--158.

[102]

X. H. Wang, D. Q. Zhang, T. Gu, and H. K. Pung. 2004. Ontology based context modeling and reasoning using OWL. In Workshop Proceedings of the 2nd IEEE Conference on Pervasive Computing and Communications.

Digital Library

[103]

W3C Group. 2010. Task Meta Models. Retreived from http://www.w3.org/2005/Incubator/model-based-ui/wiki/Task_Meta_Models.

[104]

Lu Xia, Chia-Chih Chen, and J. K. Aggarwal. 2011. Human detection using depth information by Kinect. In Proceedings of the 2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 15--22.

[105]

Stephen S. Yau and Junwei Liu. 2006. Hierarchical Situation Modeling and Reasoning for Pervasive Computing. In Proceedings of the the 4th IEEE Workshop on Software Technologies for Future Embedded and Ubiquitous Systems, and the 2nd International Workshop on Collaborative Computing, Integration, and Assurance (SEUS-WCCIA’06). IEEE Computer Society, Washington, DC, 5--10.

Digital Library

[106]

YoungTaek Jin Yun Her and Su-Kyoung Kim. 2010. A context-aware framework using ontology for smart phone platform. International Journal of Digital Content Technology and Its Applications 4, 5.

[107]

Dong Zhang Dong Zhang, D. Gatica-Perez, S. Bengio, and I. McCowan. 2006. Modeling individual and group actions in meetings with layered HMMs. Retrieved from http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm&quest;arnumber=1632036.

[108]

Huiyu Zhou and Huosheng Hu. 2008. Human motion tracking for rehabilitation, a survey. Biomedical Signal Processing and Control 3, 1 (2008), 1--18.

Cited By

Horváth ITepjit S(2024)A synthetic agent to simulate decisional behaviour of designers working with an active recommender framework systemJournal of Integrated Design & Process Science10.3233/JID-22001527:2(83-109)Online publication date: 19-Mar-2024
https://dl.acm.org/doi/10.3233/JID-220015
Chen WYu ZYang CLu Y(2024)Abnormal Behavior Recognition Based on 3D Dense ConnectionsInternational Journal of Neural Systems10.1142/S012906572450049734:09Online publication date: 16-Jul-2024
https://doi.org/10.1142/S0129065724500497
Zhang WYu GDeng S(2024)Human behavior recognition method based on wearable devicesJournal of Physics: Conference Series10.1088/1742-6596/2858/1/0120462858:1(012046)Online publication date: 1-Oct-2024
https://doi.org/10.1088/1742-6596/2858/1/012046
Show More Cited By

Index Terms

A survey on ontologies for human behavior recognition

Recommendations

A tutorial on human activity recognition using body-worn inertial sensors

The last 20 years have seen ever-increasing research activity in the field of human activity recognition. With activity recognition having considerably matured, so has the number of challenges in designing, implementing, and evaluating activity ...
1st workshop on human factors and activity recognition in healthcare, wellness and assisted living: recognise2interact
UbiComp '13 Adjunct: Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication

Context-aware systems have the potential to revolutionize the way humans interact with information technology. The first workshop on Human Factors and Activity Recognition in Healthcare, Wellness and Assisted Living (Recognise2Interact) aims to enable ...
Fuzzy system based human behavior recognition by combining behavior prediction and recognition

Our method can show plural recognition results, i.e. person is waving while walking.We propose behavior recognition fusing current recognition and prediction of behavior.For the fusion, the fuzzy system based classifier of behaviors is adopted. With the ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Computing Surveys

ACM Computing Surveys Volume 46, Issue 4

April 2014

463 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/2597757

Issue’s Table of Contents

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 March 2014

Accepted: 01 August 2013

Revised: 01 March 2013

Received: 01 December 2012

Published in CSUR Volume 46, Issue 4

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

115
Total Citations
View Citations
7,122
Total Downloads

Downloads (Last 12 months)275
Downloads (Last 6 weeks)44

Reflects downloads up to 12 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Horváth ITepjit S(2024)A synthetic agent to simulate decisional behaviour of designers working with an active recommender framework systemJournal of Integrated Design & Process Science10.3233/JID-22001527:2(83-109)Online publication date: 19-Mar-2024
https://dl.acm.org/doi/10.3233/JID-220015
Chen WYu ZYang CLu Y(2024)Abnormal Behavior Recognition Based on 3D Dense ConnectionsInternational Journal of Neural Systems10.1142/S012906572450049734:09Online publication date: 16-Jul-2024
https://doi.org/10.1142/S0129065724500497
Zhang WYu GDeng S(2024)Human behavior recognition method based on wearable devicesJournal of Physics: Conference Series10.1088/1742-6596/2858/1/0120462858:1(012046)Online publication date: 1-Oct-2024
https://doi.org/10.1088/1742-6596/2858/1/012046
Zhang WYu GDeng S(2024)Research on TCN Model Based on SSARF Feature Selection in the Field of Human Behavior RecognitionIET Biometrics10.1049/2024/49822772024:1Online publication date: 30-Sep-2024
https://doi.org/10.1049/2024/4982277
Abonyi JNagy LRuppert TAbonyi JNagy LRuppert T(2024)Introduction to the Industrial Application of Semantic TechnologiesOntology-Based Development of Industry 4.0 and 5.0 Solutions for Smart Manufacturing and Production10.1007/978-3-031-47444-6_2(23-65)Online publication date: 1-Jan-2024
https://doi.org/10.1007/978-3-031-47444-6_2
Wongchomphu PBeokhaimook C(2023)SCA Advice System: Ontology Framework for a Computer Curricula Advice System Based on Student BehaviorJournal of information and communication convergence engineering10.56977/jicce.2023.21.4.30621:4(306-315)Online publication date: 31-Dec-2023
https://doi.org/10.56977/jicce.2023.21.4.306
Moulouel KChibani AAmirat Y(2023)Ontology-based hybrid commonsense reasoning framework for handling context abnormalities in uncertain and partially observable environmentsInformation Sciences10.1016/j.ins.2023.02.078631(468-486)Online publication date: Jun-2023
https://doi.org/10.1016/j.ins.2023.02.078
Dave DBagi R(2023)LightHARs: A Light Human Activity Recognition SystemProceedings of 3rd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications10.1007/978-981-19-6088-8_39(447-456)Online publication date: 24-Feb-2023
https://doi.org/10.1007/978-981-19-6088-8_39
Rasmusen SPenz MWidauer SNako PKurteva ARoa-Valverde AFensel A(2022)Raising Consent Awareness With Gamification and Knowledge GraphsInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.30082018:1(1-21)Online publication date: 3-Jun-2022
https://dl.acm.org/doi/10.4018/IJSWIS.300820
Song RWen YTao WZhang QPapadimitriou Evan Gelder P(2022)Semantic Modeling of Ship Behavior in Cognitive SpaceJournal of Marine Science and Engineering10.3390/jmse1010134710:10(1347)Online publication date: 22-Sep-2022
https://doi.org/10.3390/jmse10101347
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

Media

Figures

Other

Tables

View Issue’s Table of Contents