Gesture-based hybrid approach for HCI in ambient intelligent environmments

In this paper we propose a novel interaction approach, based on gestures, aiming to recognize and enhance interactions between augmented human beings and augmented environments. We explain how this model, we called ARAMIS, allows interaction designers to fill the gap between real and virtual worlds augmenting the human itself. An enhanced interaction is achieved exploiting a hybrid approach. This approach is defined hybrid since it is the combination of several complementary techniques: wearable and pervasive computing paradigms, brute force, fuzzy and ML methods, virtual and real worlds, optical and non-optical sensing technologies. A framework implementing this concept has been developed. Finally, in order to validate our approach, we present a first prototype implemented according to the ARAMIS concept.

[1]  D. Leo,et al.  Blindness, fear of sight loss, and suicide. , 1999, Psychosomatics.

[2]  Lawrence J. Mazlack,et al.  Approximate Representations in the Medical Domain , 2010, 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[3]  Roxana Gîrju,et al.  Automatic Detection of Causal Relations for Question Answering , 2003, ACL 2003.

[4]  Thomas Pederson,et al.  Towards an Activity-Aware Wearable Computing Platform Based on an Egocentric Interaction Model , 2007, UCS.

[5]  Diane J. Cook,et al.  How smart are our environments? An updated look at the state of the art , 2007, Pervasive Mob. Comput..

[6]  Nelson Minar,et al.  Wearable computing meets ubiquitous computing: reaping the best of both worlds , 1999, Digest of Papers. Third International Symposium on Wearable Computers.

[7]  Wai Lam,et al.  Extracting causation knowledge from natural language texts , 2005 .

[8]  Pietro Polotti,et al.  Tangible Acoustic Interfaces and their Applications for the Design of New Musical Instruments , 2005, NIME.

[9]  Wray L. Buntine.  A Guide to the Literature on Learning Probabilistic Networks from Data , 1996, IEEE Trans. Knowl. Data Eng..

[10]  Maria Karam,et al.  A framework for research and design of gesture-based human-computer interactions , 2006 .

[11]  S. Mitra,et al.  Gesture Recognition: A Survey , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[12]  Robin D. Everall,et al.  The Teen Suicide Research Project. , 2001 .

[13]  Yang Li,et al.  Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes , 2007, UIST.

[14]  Leigh Roeger,et al.  Perceived Academic Performance as an Indicator of Risk of Attempted Suicide in Young Adolescents , 2005, Archives of suicide research : official journal of the International Academy for Suicide Research.

[15]  Masafumi Hagiwara,et al.  Extended fuzzy cognitive maps , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[16]  Ayoub Al-Hamadi,et al.  A Hidden Markov Model-Based Isolated and Meaningful Hand Gesture Recognition , 2008 .

[17]  Nicolai Marquardt,et al.  Proxemic interactions: the new ubicomp? , 2011, INTR.

[18]  Sven Barnow,et al.  Suicidality and tiredness of life among very old persons: Results from the Berlin Aging Study (BASE) , 1997 .

[19]  Detlef Nauck,et al.  Foundations Of Neuro-Fuzzy Systems , 1997 .

[20]  Syin Chan,et al.  Extracting Causal Knowledge from a Medical Database Using Graphical Patterns , 2000, ACL.

[21]  Frank Stajano,et al.  Interfacing with the invisible computer , 2002, NordiCHI '02.

[22]  David W. Murray,et al.  Object recognition and localization while tracking and mapping , 2009, 2009 8th IEEE International Symposium on Mixed and Augmented Reality.

[23]  Yaonan Wang,et al.  SVM Based Adaptive Inverse Controller for Excitation Control , 2007, ISNN.

[24]  J M Hoc,et al.  From human – machine interaction to human – machine cooperation , 2000, Ergonomics.

[25]  Satoshi Sekine,et al.  Extracting Causal Knowledge Using Clue Phrases and Syntactic Patterns , 2008, PAKM.

[26]  David W. Murray,et al.  Combining monoSLAM with object recognition for scene augmentation using a wearable camera , 2010, Image Vis. Comput..

[27]  Douglas C. Engelbart,et al.  Augmenting human intellect: a conceptual framework , 1962 .

[28]  Mark Billinghurst,et al.  Applying HCI principles to AR systems design , 2007 .

[29]  A. Gopnik,et al.  Children’s imitation of causal action sequences is influenced by statistical and pedagogical evidence , 2011, Cognition.

[30]  Judea Pearl,et al.  A Theory of Inferred Causation , 1991, KR.

[31]  Kay Römer.  Time synchronization in ad hoc networks , 2001, MobiHoc '01.

[32]  Bart Kosko,et al.  Fuzzy Cognitive Maps , 1986, Int. J. Man Mach. Stud..

[33]  Gregory D. Weber,et al.  Discovering Causal Relations by Experimentation: Causal Trees , 1997 .

[34]  Sushmita Mitra,et al.  Neuro-fuzzy rule generation: survey in soft computing framework , 2000, IEEE Trans. Neural Networks Learn. Syst..

[35]  Elena Mugellini,et al.  ARAMIS: Toward a Hybrid Approach for Human- Environment Interaction , 2011, HCI.