NDLI: E-Gesture: a collaborative architecture for energy-efficient gesture recognition with hand-worn sensor and mobile devices

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E-Gesture: a collaborative architecture for energy-efficient gesture recognition with hand-worn sensor and mobile devices

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E-Gesture: a collaborative architecture for energy-efficient gesture recognition with hand-worn sensor and mobile devices

Content Provider	ACM Digital Library
Author	Yoo, Chungkuk Hwang, Inseok Lee, Jinwon Park, Taiwoo Song, Junehwa Nachman, Lama
Abstract	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.
Starting Page	260
Ending Page	273
Page Count	14
File Format	PDF MP4
ISBN	9781450307185
DOI	10.1145/2070942.2070969
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-11-01
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Mobile gesture recognition Closed-loop collaborative architecture Energy efficiency Hidden markov model
Content Type	Audio Text
Resource Type	Article

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