Gesture spotting with body-worn inertial sensors to detect user activities

被引：221

作者：

Junker, Holger ^{[1
]}

Amft, Oliver ^{[1
]}

Lukowicz, Paul ^{[2
]}

Troester, Gerhard ^{[1
]}

机构：

[1] ETH, Wearable Comp Lab, CH-8092 Zurich, Switzerland

[2] Univ Passau, Embedded Syst Grp, D-94032 Passau, Germany

来源：

PATTERN RECOGNITION | 2008年 / 41卷 / 06期

关键词：

natural gesture segmentation; gesture spotting; activity recognition; automatic dietary monitoring; event detection;

D O I：

10.1016/j.patcog.2007.11.016

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a method for spotting sporadically occurring gestures in a continuous data stream from body-worn inertial sensors. Our method is based on a natural partitioning of continuous sensor signals and uses a two-stage approach for the spotting task. In a first stage, signal sections likely to contain specific motion events are preselected using a simple similarity search. Those preselected sections are then further classified in a second stage, exploiting the recognition capabilities of hidden Markov models. Based on two case studies, we discuss implementation details of our approach and show that it is a feasible strategy for the spotting of various types of motion events. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：2010 / 2024

页数：15

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