Don't slow me down: Bringing energy efficiency to continuous gesture recognition

Proceedings - International Symposium on Wearable Computers, ISWC

Volumn , Issue , 2010, Pages

  Raffa, Giuseppe ^a   Lee, Jinwon ^b   Nachman, Lama ^a   Song, Junehwa ^b  

^a INTEL CORPORATION   (United States)

^b Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

EVALUATION RESULTS; FORM FACTORS; HAND GESTURE; MINIMAL PROCESSING; POWER SAVINGS; PROCESSING OVERHEAD; RECOGNITION ACCURACY; SENSOR DATA; TOUCH-SCREEN INTERACTION; USER INTERACTION; VISUAL ATTENTION; VOICE MAIL;

APPROXIMATION THEORY; DATA HANDLING; ENERGY EFFICIENCY; GESTURE RECOGNITION; MOBILE DEVICES; OPTIMIZATION; SENSORS; WEARABLE COMPUTERS;

PIPELINE PROCESSING SYSTEMS;

EID: 78651400818     PISSN: 15504816     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISWC.2010.5665872     Document Type: Conference Paper

References (28)

1. O. Wobbrock, A. D. Wilson, and Y. Li, "Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes", In Proc. of UIST 2007
2. H. Junker, O. Amft, P. Lukowicz, and G. Troster, "Gesture spotting with body-worn inertial sensors to detect user activities", Pattern Recognition Journal, 2007
3. J. Lin et al, "uWave: Accelerometer-based Personalized Gesture Recognition and Its Applications", PerCom, 2009
4. T. Schlomer et al, "Gesture Recognition with a Wii Controller", In Proc. of TEI, 2008
5. J. Kela et al, "Accelerometer-based gesture control for a design environment", Personal and Ubiquitous Computing Journal, 2006
6. J. Mantyjarvi, J. Kela, P. Korpipaa and S. Kallio, "Enabling fast and effortless customization in accelerometer based gesture interaction", In Proc. of MUM, 2004
7. K. Lyons et al, "GART: The Gesture and Activity Recognition Toolkit, In Proc. of HCI, 2007
8. J. Yoo, W. Hwang, S. Baek, and K. Park, "Intuitive Interface device for Wearable Computers", Next Generation PC, 2005
9. A. Benbasat and J. Paradiso, "An Inertial Measurement Framework for Gesture Recognition and Applications" In Proc. of Gesture Workshop, 2001
10. F. Hofmann et al, "Velocity profile based recognition of dynamic gestures with discrete Hidden Markov Models" In Proc. of Gesture and Sign Language in HCI, 1998.
11. H. Lee and J. Kim, "An HMM-Based Threshold Model Approach for Gesture Recognition", IEEE Transactions on Pattern Analysis and Machine Intelligence, 1999
12. J. Wu et al, "Gesture Recognition with a 3-D Accelerometer", In Proc. of Ubiquitous Intelligence and Computing, 2009
13. R. Parsan and K. Singh, "A Single Accelerometer based Wireless Embedded System for Predefined Dynamic Gesture Recognition", In Proc. of IHCI, 2009
14. A. Hein et al, "Utilizing an Accelerometric Bracelet for UbiquitousGesture-Based Interaction", In Proc. of Universal Access in Human-Computer Interaction 2009
15. S. Cho et al, "Two-stage Recognition of Raw Acceleration Signals for 3-D Gesture-Understanding Cell Phones", In Proc. of IWFHR, 2006
16. Hidden Markov Model Toolkit (HTK), http://htk.eng.cam.ac.uk/
17. Y. Wu, T. S. Huang, "Vision-Based Gesture Recognition: A Review", In Proc. of Gesture-Based Communication in Human-Computer Interaction, 1999
18. M. Kauppila et al, "Accelerometer Based Gestural Control of Browser Applications", In Proc. of UCS 2007
19. T. Pylvannainen, "Accelerometer Based Gesture Recognition Using Continuous HMMs", In Proc. of IbPRIA 2005
20. L.R. Rabiner, "A Tutorial on Hidden Markov Models and Selected Applications in Proc. IEEE Speech Recognition, vol. 77, pp. 257-286, 1989
21. M. Changxue, M.A. Randolph, J. Drish, "A support vector machines-based rejection technique for speech recognition," IEEE Acoustics, Speech, and Signal Processing, pp. 381-384, 2001
22. H. Brashear et al, "Using Multiple Sensors for Mobile Sign Language Recognition", In Proc. of ISWC 2003
23. A. Haro et al, "Mobile Camera-Based User Interaction", In Proc. of HCI/ICCV 2005.
24. R. Amstutz et al. "Performance Analysis of an HMM-Based Gesture Recognition Using a Wristwatch Device". In Proc. 2009 Conference on Computational Science and Engineering,2009
25. S. Kang et al, "SeeMon: Scalable and Energy-efficient Context Monitoring Framework for Sensor-rich Mobile Environments", In Proc. of MobiSys'08
26. P. Zappi et al, "Activity Recognition from On-Body Sensors: Accuracy-Power Trade-Off by Dynamic Sensor Selection", In Prco. of EWSN'09
27. B. French et al, "Selective Sampling Strategies to Conserve Power in Context Aware Systems", In Proc. of ISWC'07
28. A. Benbasat et al, "A Framework for the Automated Generation of Power-Efficient Classifiers for Embedded Sensor Nodes," In Proc. of SenSys'07