• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1437-1445
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• 2014

A smartphone has very limited input methods regardless of its various functions. In this respect, it is one alternative that sensor motion recognition can make intuitive and various user interface. In this paper, we recognize user's motion using acceleration sensor, magnetic field sensor, and gyro sensor in smartphone. We try to reduce sensing error by gradient descent algorithm because in single sensor it is hard to obtain correct data. And we apply vector quantization by conversion of rotation displacement to spherical coordinate system for elevated recognition rate and recognition of small motion. After vector quantization process, we recognize motion using HMM(Hidden Markov Model).

• ETRI Journal
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• v.36 no.6
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• pp.1016-1022
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• 2014

This paper presents a hybrid model solution for user motion recognition. The use of a single classifier in motion recognition models does not guarantee a high recognition rate. To enhance the motion recognition rate, a hybrid model consisting of decision trees and artificial neural networks is proposed. We define six user motions commonly performed in an indoor environment. To demonstrate the performance of the proposed model, we conduct a real field test with ten subjects (five males and five females). Experimental results show that the proposed model provides a more accurate recognition rate compared to that of other single classifiers.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.229-237
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• 2022

Motion recognition is very useful for implementing an intuitive HMI (Human-Machine Interface). In particular, hands are the body parts that can move most precisely with relatively small portion of energy. Thus hand motion has been used as an efficient communication interface with other persons or machines. In this paper, we design and implement a light-weight ANN (Artificial Neural Network)-based hand motion recognition using a state-of-the-art flex sensor. The proposed design consists of data collection from a wearable flex sensor, preprocessing filters, and a light-weight NN (Neural Network) classifier. For verifying the performance and functionality of the proposed design, we implement it on a low-end embedded device. Finally, our experiments and prototype implementation demonstrate that the accuracy of the proposed hand motion recognition achieves up to 98.7%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1103-1108
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• 2016

The development of a variety of sensor technology, users smart phone, the use of motion recognition apparatus such as a console game machines is increasing. It tends to user needs motion recognition-based input device are increasing. Existing motion recognition mouse is equipped with a modified form of the mouse button on the outside and serves as a wheel mouse left and right buttons. Existing motion recognition mouse is to manufacture a small, there is a difficulty to operate the button. It is to apply the motion recognition technology the motion recognition technology is used only pointing the cursor there is a limit. In this paper, use of MEMS-based motion recognition sensor, the body of the two-point operation data by recognizing the operation of the (thumb and forefinger) and generating a control signal, followed by studies on the generated control signal to a wireless transmitting computer input device.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.791-793
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• 2016

In the development of various types of sensor technology, the general users smartphone, the environment is increased, which can be seen in contact with the movement recognition device, such as a console game machine (Nintendo Wii), an increase in the user needs of the action recognition-based input device there is a tendency to have. Mouse existing behavior recognition, attached to the outside, is mounted in the form of mouse button is deformed, the left mouse was the role of the right button and a wheel, an acceleration sensor (or a gyro sensor) inside to, plays the role of a mouse cursor, is to manufacture a compact, there is a difficulty in operating the button, to apply a motion recognition technology is used to operate recognition technology only pointing cursor is limited. Therefore, in this paper, using a MEMS-based motion-les Koguni tion sensor (Motion Recognition Sensor), to recognize the behavior of the two points of the human body (thumb and forefinger), to generate the motion data, and this to the foundation, compared to the pre-determined matching table (moving and mouse button events cursor), and generates a control signal by determining, were studied the generated control signal input device of the computer wirelessly transmitting.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.367-372
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• 2021

The purpose of this study is to suggest that the movement expression activity of intellectually disabled people is effective in the learning process of LMA motion recognition based on Kinect sensor. We performed an ICT motion recognition games for intellectually disabled based on movement learning of LMA. The characteristics of the movement through Laban's LMA include the change of time in which movement occurs through the human body that recognizes space and the tension or relaxation of emotion expression. The design and implementation of the motion recognition model will be described, and the possibility of using the proposed motion recognition model is verified through a simple experiment. As a result of the experiment, 24 movement expression activities conducted through 10 learning sessions of 5 participants showed a concordance rate of 53.4% or more of the total average. Learning motion games that appear in response to changes in motion had a good effect on positive learning emotions. As a result of study, learning motion games that appear in response to changes in motion had a good effect on positive learning emotions

• Korean Journal of Artificial Intelligence
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• v.4 no.1
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• pp.1-3
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• 2016

These days, citizens are interested in the energy. IT technology needs to develop and to make use of energy effectively and to save energy. In this study, motion recognition LED lamp was used to have good energy efficiency and to be made of environment friendly material. The purpose of development of the lamp was to add motion recognition to LED lamp. In this study, infrared ray sensor's distance measurement was used to develop LED lamp. Most of the lamps were used under dark environment, so that infrared ray sensor was used to perceive movement under dark environment. And, LED lamp with good efficiency and less power consumption was used to increase efficiency. Citizens were interested in perception of the movement to distinguish from conventional type of the lamps.

• Journal of Korea Game Society
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• v.9 no.5
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• pp.63-72
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• 2009

I-phone presented a new mobile control type by the introducing motion recognition sensor and that influenced on game application development so that led a lot of games using kinds of sensors. In this paper, we divided the game enjoyment into 5 factors for the embodiment of the sensor's influence direction on the enjoyment. We experimented two game, which have same content, different devices in using motion recognition sensor or not for clarifying the distinction between devices. As a experiment source game, we used Cooking Mama, as a experimental device, we used I-pod touch and NDS. This experiment shows a motion recognition sensor control's enjoyment is far superior to touch sensor. This sensor got high marks on every fun factors, stimulus, absorption, empathy, accomplishment and variation. Especially, stimulus and empathy showed great differences. In this case, we found the fact that extended communication between the gamer and the device can be fun.

• Smart Media Journal
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• v.8 no.3
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• pp.47-52
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• 2019

In this paper, we designed HW / SW interfaces for processing the signals of capacitive sensors like Electric Potential Sensor (EPS) to detect the surrounding electric field disturbance as feature signals in motion recognition systems. We implemented a smart light control system with those interfaces. In the system, the on/off switch and brightness adjustment are controlled by hand gestures using the designed and fabricated interface circuits. PWM (Pulse Width Modulation) signals of the controller with a driver IC are used to drive the LED and to control the brightness and on/off operation. Using the hand-gesture signals obtained through EPS sensors and the interface HW/SW, we can not only construct a gesture instructing system but also accomplish the faster recognition speed by developing dedicated interface hardware including control circuitry. Finally, using the proposed hand-gesture recognition and signal processing methods, the light control module was also designed and implemented. The experimental result shows that the smart light control system can control the LED module properly by accurate motion detection and gesture classification.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1439-1445
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• 2013

We present a Taekwondo training system using a hybrid sensing technique of a body sensor and a visual sensor. Using a body sensor (accelerometer), rotational and inertial motion data are captured which are important for Taekwondo motion detection and evaluation. A visual sensor (camera) captures and records the sequential images of the performance. Motion chunk is proposed to structuralize Taekwondo motions and design HMM (Hidden Markov Model) for motion recognition. Trainees can evaluates their trial motions numerically by computing the distance to the standard motion performed by a trainer. For motion training video, the real-time video images captured by a camera is overlayed with a visualized body sensor data so that users can see how the rotational and inertial motion data flow.