An Accelerometer-Based Digital Pen With a Trajectory Recognition Algorithm for Handwritten Digit and Gesture Recognition

Wang, Jeen-Shing; Chuang, Fang-Chen

doi:10.1109/tie.2011.2167895

Cited by 142 publications

(70 citation statements)

References 18 publications

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“…The reviewed methods of similarity measurement include Dynamic Time Warping (DTW) [1], Longest Common Subsequence (LCS) [31], Protractor3D [17] and Levenshtein edit distance [11]. On the other hand, the reviewed statistical methods model the motions in a probabilistic manner such as Hidden Markov Models (HMMs) [5,18,37], or are based on probabilistic theory, like Probabilistic Neural Network (PNN) [34] which tries to asymptotically approach the Bayes optical decision surface. The authors in [17] argue that the template-based approaches perform well even with few training samples and they are easier to implement and deploy on different types of devices since they do not require specialized libraries.…”

Section: Gesture Recognition Techniquesmentioning

confidence: 99%

A gesture-based method for natural interaction in smart spaces

Wang

Bernardos

Besada

et al. 2015

AIS

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Abstract.A key issue when making spaces smart is the availability of satisfying and personalized interaction methods, for the user to comfortably manage the physical and virtual resources in the environment. Among the multiple interaction approaches that are nowadays being explored with this objective, gesture-based ones seem to have a great potential. In this line, this research describes a gesture-based interaction method that uses a specific grammar to control and network objects in a smart space. The method's grammar establishes that the user has to identify the object to interact with by performing an individuation gesture primitive (the object's initial letter), then using an action gesture primitive to indicate the action to perform. The action may involve a second object, which will be identified as the first one. The ímer will be able to personalize the action gestures in the vocabulary, and to configure the commands assigned to gestures, and the system will provide interaction cues for the user not to feel lost. The main component of the system is a gesture recognition module based on an adapted Dynamic Time Warping algorithm. This module works sharply on acceleration or position data inputs, being suitable to deploy device instrumented or infrastructure-based solutions for gesture recognition (i.e. smartphone or Kinect-based ones). The average recognition rate is 93.63% for smartphone-based recognition and 98.64% for Kinect-based one, respectively. The paper also details the architecture and software tools that enables the interaction method to work in a real environment.

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Section: Gesture Recognition Techniquesmentioning

confidence: 99%

A gesture-based method for natural interaction in smart spaces

Wang

Bernardos

Besada

et al. 2015

AIS

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“…The investigational consequences have successfully validated the success of the trajectory detection algorithm for handwritten digit and gesture recognition using the proposed product. [2] In this research work a health monitoring of human physiological signals such as temperature and pulse using ZigBee is formed in this work, by this device the temperature and pulse of humans can be observe from a distant location, and some abnormalities can be easily indicated via SMS .The measurements obtain from the temperature sensor and heart beat sensor are send to the PC through ZigBee module. The PC collects the information and also sends SMS, to the indicated mobile number through a GSM module.…”

Section: Related Workmentioning

confidence: 99%

Design and Development of WRIST-TILT Based PC Cursor Control Using Accelerometer

Nayyar¹,

Lenka²

2013

IJCSEA

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“…The inertial-sensor-based input devices can provide the coordinate information of the pen tip as functions of time for online handwriting recognition [1], [2]. A significant advantage of inertial-sensor-based input devices for handwriting recognition is that they can be operated without any external reference or ambit restrictions [1], [2], [3], [4]. Recently, many researchers have focused on the development of inertial-sensor-based input device.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, many researchers have focused on the development of inertial-sensor-based input device. To name a few, Wang and Chuang [4] presented an accelerometerbased digital pen with a trajectory recognition algorithm for 2D handwritten digit recognition. The proposed algorithm extracted the time-and frequency-domain features from the accelerations, and then selected the most important features by the kernel-based class separability (KBCS) and linear discriminant analysis (LDA).…”

Section: Introductionmentioning

confidence: 99%

Online Handwriting Recognition Using an Accelerometer-Based Pen Device

Wang

Hsu

Chu³

2013

Proceedings of the 2nd International Conference on Advances in Computer Science and Engineering

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Abstract-This paper presents an accelerometer-based pen device for online handwriting recognition applications. The accelerometer-based pen device consists of a triaxial accelerometer, a microcontroller, and an RF wireless transmission module. Users can hold the pen device to write numerals in air without space limitations. The accelerations generated by hand motions are generated by the accelerometer embedded in the pen device, and are transmitted to a personal computer for further signal preprocess via the wireless module. Subsequently, a dynamic time warping (DTW) algorithm is applied to align the accelerations and search class templates for each digit in the training stage. Finally, the accelerations can be recognized via the alignment with the class templates in the testing stage. The average user-dependent and userindependent recognition rates were 90.6% and 84.8%, respectively. Our experimental results have successfully validated the effectiveness of the accelerometer-based pen device for 3-dimensional (3-D) online handwriting recognition. IndexTerms-Onlinehandwriting recognition, accelerometer-based input device, dynamic time warping.

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An Accelerometer-Based Digital Pen With a Trajectory Recognition Algorithm for Handwritten Digit and Gesture Recognition

Cited by 142 publications

References 18 publications

A gesture-based method for natural interaction in smart spaces

A gesture-based method for natural interaction in smart spaces

Design and Development of WRIST-TILT Based PC Cursor Control Using Accelerometer

Online Handwriting Recognition Using an Accelerometer-Based Pen Device

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