Sitting Posture Recognition and Location Estimation for Human-Aware Environment

Realization of human-computer symbiosis is an important idea in the context of ubiquitous computing. Symbiotic Computing is a concept that bridges the gap between situations in Real Space RS and data in Digital Space DS. The main purpose is to develop an intelligent software application as well as establish the next generation information platform to develop the symbiotic system. In this paper, the authors argue that it is necessary to build 'Mutual Cognition' between human and system. Mutual cognition consists of two functions: 'RS Cognition' and 'DS Cognition'. This paper examines RS Cognition, which consists of many software functions for perceiving various situations like events or humans' activities in RS. The authors develop two perceptual functions, sitting posture recognition and human's location estimation for a person, as RS perception tasks. In the resulting experiments, developed functions are quite competent to recognize a human's activities.

[1]  Peter J. Hawrylak,et al.  Techniques to Model and Derive a Cyber-Attacker’s Intelligence , 2013 .

[2]  Kenji Sugawara,et al.  Concept of Symbiotic Computing and its Agent-Based Application to a Ubiquitous Care-Support Service , 2009, Int. J. Cogn. Informatics Nat. Intell..

[3]  Stevan Harnad,et al.  Symbol grounding problem , 1990, Scholarpedia.

[4]  Shigeru Fujita,et al.  A design of cognitive agents for recognizing real space — towards symbiotic computing — , 2008, 2008 7th IEEE International Conference on Cognitive Informatics.

[5]  Hiroshi Mizoguchi,et al.  Robotic room: Symbiosis with human through behavior media , 1996, Robotics Auton. Syst..

[6]  Stefan Poslad,et al.  Ubiquitous Computing: Smart Devices, Environments and Interactions , 2009 .

[7]  Barry Brumitt,et al.  EasyLiving: Technologies for Intelligent Environments , 2000, HUC.

[8]  Mark Weiser.  The computer for the 21st century , 1991 .

[9]  Juan Barceló,et al.  Computational Intelligence in Archaeology , 2008 .

[10]  Gregory D. Abowd,et al.  The Aware Home: A Living Laboratory for Ubiquitous Computing Research , 1999, CoBuild.

[11]  Eduardo Alonso,et al.  Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications , 2010 .

[12]  Yingxu Wang.  Breakthroughs in Software Science and Computational Intelligence , 2012 .

[13]  Bill N. Schilit,et al.  Disseminating active map information to mobile hosts , 1994, IEEE Network.

[14]  T. Hasegawa,et al.  A structured environment with sensor networks for intelligent robots , 2008, 2008 IEEE Sensors.

[15]  J. C. R. Licklider,et al.  Man-Computer Symbiosis , 1960 .

[16]  Larry Rudolph,et al.  Project Oxygen: Pervasive, Human-Centric Computing - An Initial Experience , 2001, CAiSE.

[17]  Bojan Cukic,et al.  A Statistical Framework for the Prediction of Fault-Proneness , 2007 .

[18]  Du Zhang.  On Localities of Knowledge Inconsistency , 2011, Int. J. Softw. Sci. Comput. Intell..

[19]  Juan A. Barceló,et al.  "Automated" Archaeology: A Useless Endeavor, an Impossible Dream, or Reality? , 2009 .

[20]  Michael H. Coen,et al.  Design Principles for Intelligent Environments , 1998, AAAI/IAAI.

[21]  Takashi Suehiro,et al.  Sensorized environment for self-communication based on observation of daily human behavior , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[22]  Shigeru Fujita,et al.  A Framework for Perceptual Functions of Symbiotic Computing , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[23]  Hideki Hashimoto,et al.  Physical agent for sensored, networked and thinking space , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[24]  A. B. M. Shawkat Ali,et al.  Multidisciplinary Computational Intelligence Techniques: Applications in Business, Engineering, and Medicine , 2012 .

[25]  Jacek M. Zurada,et al.  Efficiency and Scalability Methods for Computational Intellect , 2013 .

[26]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[27]  Stefano Ferilli,et al.  FOL Learning for Knowledge Discovery in Documents , 2010 .

[28]  Mary Czerwinski,et al.  The New EasyLiving Project at Microsoft Research , 1998 .

[29]  Joo-Ho Lee,et al.  Intelligent Space — concept and contents , 2002, Adv. Robotics.

[30]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[31]  Lei Xu,et al.  Learning Algorithms for RBF Functions and Subspace Based Functions , 2012 .

[32]  Shuang Liang,et al.  Cognitive Garment Panel Design Based on BSG Representation and Matching , 2012, Int. J. Softw. Sci. Comput. Intell..

[33]  M. Weiser.  The Computer for the Twenty-First Century , 1991 .

[34]  A. Pentland.  Smart rooms, smart clothes , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[35]  Shigeru Fujita,et al.  A concept of context-aware computing based on symbol grounding perspective , 2010, 2010 2nd International Symposium on Aware Computing.

[36]  Yingxu Wang.  Advances in Abstract Intelligence and Soft Computing , 2012 .

[37]  Du Zhang,et al.  A Value-Based Framework for Software Evolutionary Testing , 2011, Int. J. Softw. Sci. Comput. Intell..

[38]  Shigeru Fujita,et al.  A Concept of Symbiotic Computing and its Application to Telework , 2007, 6th IEEE International Conference on Cognitive Informatics.

[39]  Du Zhang,et al.  Advances in Machine Learning Applications in Software Engineering , 2007 .

[40]  Norio Shiratori,et al.  Agent-Based Middleware for Advanced Communication Services in a Ubiquitous Computing Environment , 2010, Int. J. Softw. Sci. Comput. Intell..

[41]  Gregory D. Abowd,et al.  Towards a Better Understanding of Context and Context-Awareness , 1999, HUC.

[42]  D. P. Acharjya,et al.  Global Trends in Intelligent Computing Research and Development , 2013 .

[43]  Siddhivinayak Kulkarni,et al.  Machine Learning Algorithms for Problem Solving in Computational Applications: Intelligent Techniques , 2012 .

[44]  Fuchun Sun,et al.  Four-Channel Control Architectures for Bilateral and Multilateral Teleoperation , 2011, Int. J. Softw. Sci. Comput. Intell..

[45]  Mohamed Abid,et al.  Medical Image Classification Using an Optimal Feature Extraction Algorithm and a Supervised Classifier Technique , 2011, Int. J. Softw. Sci. Comput. Intell..