An HMM-Based Threshold Model Approach for Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
XWand: UI for intelligent spaces
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Vision-Based Gesture Recognition: A Review
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
An Inertial Measurement Framework for Gesture Recognition and Applications
GW '01 Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction
Self-contained Spatial Input Device for Wearable Computers
ISWC '03 Proceedings of the 7th IEEE International Symposium on Wearable Computers
SATIRE: a software architecture for smart AtTIRE
Proceedings of the 4th international conference on Mobile systems, applications and services
Accelerometer-based gesture control for a design environment
Personal and Ubiquitous Computing
Gesture connect: facilitating tangible interaction with a flick of the wrist
Proceedings of the 1st international conference on Tangible and embedded interaction
Gesture spotting with body-worn inertial sensors to detect user activities
Pattern Recognition
Gesture recognition with a Wii controller
Proceedings of the 2nd international conference on Tangible and embedded interaction
Proceedings of the 6th international conference on Mobile systems, applications, and services
Gestures are strings: efficient online gesture spotting and classification using string matching
Proceedings of the ICST 2nd international conference on Body area networks
The Gesture Watch: A Wireless Contact-free Gesture based Wrist Interface
ISWC '07 Proceedings of the 2007 11th IEEE International Symposium on Wearable Computers
A framework of energy efficient mobile sensing for automatic user state recognition
Proceedings of the 7th international conference on Mobile systems, applications, and services
uWave: Accelerometer-based personalized gesture recognition and its applications
PERCOM '09 Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications
Performance Analysis of an HMM-Based Gesture Recognition Using a Wristwatch Device
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 02
Mercury: a wearable sensor network platform for high-fidelity motion analysis
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
GART: the gesture and activity recognition toolkit
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
Mobile camera-based user interaction
ICCV'05 Proceedings of the 2005 international conference on Computer Vision in Human-Computer Interaction
MobiCon: a mobile context-monitoring platform
Communications of the ACM
CoMon: cooperative ambience monitoring platform with continuity and benefit awareness
Proceedings of the 10th international conference on Mobile systems, applications, and services
SymPhoney: a coordinated sensing flow execution engine for concurrent mobile sensing applications
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
SocioPhone: everyday face-to-face interaction monitoring platform using multi-phone sensor fusion
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
BOSS: building operating system services
nsdi'13 Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation
Maximum likelihood analysis of conflicting observations in social sensing
ACM Transactions on Sensor Networks (TOSN)
| Hi-index | 0.02 |
Gesture is a promising mobile User Interface modality that enables eyes-free interaction without stopping or impeding movement. In this paper, we present the design, implementation, and evaluation of E-Gesture, an energy-efficient gesture recognition system using a hand-worn sensor device and a smartphone. E-gesture employs a novel gesture recognition architecture carefully crafted by studying sporadic occurrence patterns of gestures in continuous sensor data streams and analyzing the energy consumption characteristics of both sensors and smartphones. We developed a closed-loop collaborative segmentation architecture, that can (1) be implemented in resource-scarce sensor devices, (2) adaptively turn off power-hungry motion sensors without compromising recognition accuracy, and (3) reduce false segmentations generated from dynamic changes of body movement. We also developed a mobile gesture classification architecture for smartphones that enables HMM-based classification models to better fit multiple mobility situations.