Smartphone Accelerometer-Based Gesture Recognition and its Robotic Application

Nam, Sangha; Kim, Joohee; Heo, Se-Kyeong; Kim, In-Cheol

doi:10.3745/ktsde.2013.2.6.395

Cited by 6 publications

(4 citation statements)

References 7 publications

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“…There have been previous reports on utilizing the IMUs of smartphones for robotics [24], especially also for Simultaneous Localization and Mapping (SLAM) [25]. Another aspect is the calibration of the IMUs [26].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Smartphone IMUs for Small Mobile Search and Rescue Robots

Zhi,

Xu,

Schwertfeger

2019

Preprint

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Small mobile robots are an important class of Search and Rescue Robots. Integrating all required components into such small robots is a difficult engineering task. Smartphones have already been made small, lightweight and cheap by the industry and are thus an excellent candidate as main controller for such robots. In this paper we outline how ROS can be used on Android devices and then evaluate one sensor which is very important for mobile robots: the Inertial Measurement Unit (IMU). Experiments are performed under static and dynamic conditions to measure the error of the IMUs of three smartphones and three professional IMUs. In the experiments we make use of a tracking system and an autonomous mobile robot.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Smartphone IMUs for Small Mobile Search and Rescue Robots

Zhi,

Xu,

Schwertfeger

2019

Preprint

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“…10) 는 DTW와 k-최근접 이웃 알고리즘을 사용하여 수행하였다 [4]. Ko외 3인은 다수의 센서들로부터 생성된 다차원 데이 터 시컨스들에 대해 시간적 융합을 시도하고 이에 대해 DTW를 적용하여 사용자의 행위를 추정하는 연구를 발표했 고 [5], Gillian외 2인은 다차원 DTW 알고리즘을 사용하여 음악적 제스처에 대한 인식을 시도했다 [6].…”

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Feature-Strengthened Gesture Recognition Model Based on Dynamic Time Warping for Multi-Users

Lee¹,

Um²,

Kwon³

2016

KIPS Transactions on Software and Data Engineering

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FsGr model, which has been proposed recently, is an approach of accelerometer-based gesture recognition by applying DTW algorithm in two steps, which improved recognition success rate. In FsGr model, sets of similar gestures will be produced through training phase, in order to define the notion of a set of similar gestures. At the 1st attempt of gesture recognition, if the result turns out to belong to a set of similar gestures, it makes the 2nd recognition attempt to feature-strengthened parts extracted from the set of similar gestures. However, since a same gesture show drastically different characteristics according to physical traits such as body size, age, and sex, FsGr model may not be good enough to apply to multi-user environments. In this paper, we propose FsGrM model that extends FsGr model for multi-user environment and present a program which controls channel and volume of smart TV using FsGrM model.

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“…Technologies recognizing user movements through acceleration sensor are applicable in various fields. Better yet, along with gyro sensor, the acceleration sensor can display the information on movements and rotation of the smart phone in number terms, which facilitates many research efforts [1][2][3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, there are a lot of studies going on about recognizing user behaviors based on smart devices. Especially in the case of smart phones, with various built-in sensors, the focus of many researchers is on developing convenient user interfaces [1][2][3][4][5][6][7][8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%