The Optimization of Interface Interactivity using Gesture Prediction Engine

Mahdi Babaei, Wong Chee Onn, Lim Yan Peng

Abstract


The primary objective of this project is to develop a gesture recognition engine for interactive interfaces using Microsoft Kinect device. A photo album is a sample of daily-use applications that is capable of having interactive interface. In this project there are features implemented to help users to view and edit their photos on the easier way. Although the 3D interface of photo album increases the reality and easy to use, simplicity of natural gestures which are recognizing by the gesture recognition engine eases the interaction. The contribution of this project is simultaneous work of a prediction and recognition engine. The algorithm benefits a Hidden Markov Model (HMM) state machine to record, update and calculate the occurrence probability of each gesture as a state in relation with previous states. It also aims to solve a major problem of interaction with the same applications which were their dependence on using devices physically and touch them directly. The optimized model had tested in an interactive digital space.


Keywords


Gesture recognition; photo album; gesture prediction; microsoft kinect; human computer interaction; smart interactivity

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References


Chu, C.W. and Cohen, I. 2005. Posture and Gesture Recognition Using 3D Body Shapes Decomposition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 69–69.

Takahashi, T. and Kishino, F. 1991. Hand Gesture Coding Based on Experiments Using a Hand Gesture Interface Device. ACM SIGCHI Bulletin: 23: 67–74.

Zimmerman, T.G., Lanier, J., Blanchard, C., Bryson, S. and Harvill, Y. 1987. A hand gesture interface device. ACM SIGCHI Bulletin. 18: 189–192.

Nanayakkara, S., Shilkrot, R., Yeo, K. P. and Maes, P. 2013. Eyering: A Finger-Worn Input Device for Seamless Interactions with our Surroundings. Proceedings of the 4th Augmented Human International Conference. 13–20.

Mitra, S. and Acharya, T.2007.Gesture recognition: A Survey. IEEE Transactions on Systems, Man, and Cybernetics. 37: 311–324.

Pavlovic, V. I., Sharma, R. and Huang, T. S.1997. Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review. IEEE Transactions on Pattern Analysis and Machine Intelligence. 19: 677–695.

Mistry, P. and Maes, P. 2009. Sixth Sense. TED India.

Oikonomidis, I., Kyriazis, N. and Argyros, A. 2011. Efficient Model-Based 3D Tracking of Hand Articulations Using Kinect. British Machine Vision Conference. 1: 1–11.

Gonzalez, R.C. and Woods, R.E. 1992. Digital Image Processing. Addison-Wesley Reading.

Webb, J. and Ashley, J.2012. Beginning Kinect Programming with the Microsoft Kinect SDK. Apress.

Gavrila, D. M.1999.The Visual Analysis of Human Movement: A Survey. Computer Vision and Image Understanding. 73: 82–98.

Aggarwal, J. K. and Cai, Q. 1997. Human Motion Analysis: A Review. IEEE Nonrigid and Articulated Motion Workshop Proceedings. 90–102.

Sumar, L. and Bainbridge-Smith, A. 2011. Feasability of Fast Image Processing Using Multiple Kinect Cameras on a Portable Platform. Department of Electrical and Computer Engineering, Univ. Canterbury, New Zealand. 3(6).

Khoshelham, K.2011. Accuracy Analysis of Kinect Depth Data. ISPRS Workshop Laser Scanning.1.

Hai, H., Bin, L., BenXiong, H. and Yi, C. 2011. Interaction System of Treadmill Games based on Depth Maps and CAM-Shift. IEEE 3rd International Conference on Communication Software and Networks. 219–222.

Yamato, J., Ohya, J. and Ishii, K. 1992. Recognizing Human Action in Time-Sequential Images using Hidden Markov Model. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Proceedings. 379–385.

Rabiner, L. R. 1989. A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. Proceedings of the IEEE. 77: 257–286.

Deshpande, M. and Karypis, G. 2004. Selective Markov Models for Predicting Web Page Accesses. ACM Transactions on Internet Technology (TOIT). 4: 163–184.




DOI: http://dx.doi.org/10.11113/jt.v68.2909

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