Accelerometer-based gesture control for a design environment

Accelerometer-based gesture control is studied as a supplementary or an alternative interaction modality. Gesture commands freely trainable by the user can be used for controlling external devices with handheld wireless sensor unit. Two user studies are presented. The first study concerns finding gestures for controlling a design environment (Smart Design Studio), TV, VCR, and lighting. The results indicate that different people usually prefer different gestures for the same task, and hence it should be possible to personalise them. The second user study concerns evaluating the usefulness of the gesture modality compared to other interaction modalities for controlling a design environment. The other modalities were speech, RFID-based physical tangible objects, laser-tracked pen, and PDA stylus. The results suggest that gestures are a natural modality for certain tasks, and can augment other modalities. Gesture commands were found to be natural, especially for commands with spatial association in design environment control.

[1]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[2]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[3]  Günter Hommel,et al.  Velocity Profile Based Recognition of Dynamic Gestures with Discrete Hidden Markov Models , 1997, Gesture Workshop.

[4]  Shuji Hashimoto,et al.  Gesture recognition using an acceleration sensor and its application to musical performance control , 1997 .

[5]  Tapio Seppänen,et al.  A dictionary-adaptive speech driven user interface for a distributed multimedia platform , 1999, Proceedings 25th EUROMICRO Conference. Informatics: Theory and Practice for the New Millennium.

[6]  S. Kay,et al.  Can detectability be improved by adding noise? , 2000, IEEE Signal Processing Letters.

[7]  Tapio Seppänen,et al.  Hand gesture recognition of a mobile device user , 2000, 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532).

[8]  Maribeth Gandy Coleman,et al.  The Gesture Pendant: A Self-illuminating, Wearable, Infrared Computer Vision System for Home Automation Control and Medical Monitoring , 2000, Digest of Papers. Fourth International Symposium on Wearable Computers.

[9]  Jun Rekimoto,et al.  GestureWrist and GesturePad: unobtrusive wearable interaction devices , 2001, Proceedings Fifth International Symposium on Wearable Computers.

[10]  Vtt Publications,et al.  Discrete hidden Markov models with application to isolated user-dependent hand gesture recognition , 2001 .

[11]  Ho-Sub Yoon,et al.  Hand gesture recognition using combined features of location, angle and velocity , 2001, Pattern Recognit..

[12]  Stephen A. Brewster,et al.  Gestural and audio metaphors as a means of control for mobile devices , 2002, CHI.

[13]  Arto Ylisaukko-oja,et al.  SoapBox: A Platform for Ubiquitous Computing Research and Applications , 2002, Pervasive.

[14]  K. Tsukada,et al.  Ubi-Finger : Gesture Input Device for Mobile Use , 2002 .

[15]  Steven A. Shafer,et al.  XWand: UI for intelligent spaces , 2003, CHI '03.

[16]  Jani Mäntyjärvi,et al.  Sensor-based context recognition for mobile applications , 2003 .

[17]  Heikki Ailisto,et al.  A Physical Selection Paradigm for Ubiquitous Computing , 2003, EUSAI.

[18]  Jani Mäntyjärvi,et al.  Online gesture recognition system for mobile interaction , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[19]  Jani Mäntyjärvi,et al.  Enabling fast and effortless customisation in accelerometer based gesture interaction , 2004, MUM '04.

[20]  Giulio Jacucci,et al.  Computational support to record and re-experience visits , 2004, Personal and Ubiquitous Computing.

[21]  Sergios Theodoridis,et al.  Pattern Recognition, Third Edition , 2006 .