• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2595-2600
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• 2012

In this study, we propose the new interface system for the disabled and old people who do not well using electronic equipment that is used physical switch interface system. The proposed new interface system is consisted of speech and motion recognition system. Speech recognition system is mike in the headset, and motion recognition system is 3-axis accelerometer in the headset. In order to verify the usefulness of the proposed system, we make an experiment on new interface.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.47-57
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• 2022

Demands for tangible contents using VR/AR technologies are much bigger as contactless services such as sports, physical activity, and fitness are expanded after COVID-19. A variety of technologies such as an offer and analysis of tangible data through a sensor technology, users' physical movement sensing through a motion recognition sensor, a real-time measurement of a physical skeleton point a multiple access to a real-time video, and AI training are being utilized as main technologies. This case study utilized motion recognition technologies as the study on tangible contents necessary for indoor-based physical education, sports, and fitness in the contactless environment and suggested cases to develop the physical measurement contents by design approach for the measurement assessment necessary for the development in tangible contents. The research established lists of the measurement assessment based on professionals' consultations within the measurement assessment function through the test to plan tangible contents and developed tangible contents by reflecting them as assessment measurement elements of tangible contents. The research can be utilized as the design approach of industrial companies which intend to develop tangible contents as well as reference cases of the research on contactless tangible contents for the sports and physical education.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.121-129
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• 2015

This paper presents a multiple vehicle recognition algorithm based on radar and vision sensor fusion for lane change assistance. To determine whether the lane change is possible, it is necessary to recognize not only a primary vehicle which is located in-lane, but also other adjacent vehicles in the left and/or right lanes. With the given sensor configuration, two challenging problems are considered. One is that the guardrail detected by the front radar might be recognized as a left or right vehicle due to its genetic characteristics. This problem can be solved by a guardrail recognition algorithm based on motion and shape attributes. The other problem is that the recognition of rear vehicles in the left or right lanes might be wrong, especially on curved roads due to the low accuracy of the lateral position measured by rear radars, as well as due to a lack of knowledge of road curvature in the backward direction. In order to solve this problem, it is proposed that the road curvature measured by the front vision sensor is used to derive the road curvature toward the rear direction. Finally, the proposed algorithm for multiple vehicle recognition is validated via field test data on real roads.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.684-691
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• 2006

As many functionalities such as cameras and MP3 players are converged to mobile phones, more intuitive and interesting interaction methods are essential. In this paper, we present applications and their enabling technologies for gesture interactive cell phones. They employ gesture recognition and real-time shake detection algorithm for supporting motion-based user interface and entertainment applications respectively. The gesture recognition algorithm classifies users' movement into one of predefined gestures by modeling basic components of acceleration signals and their relationships. The recognition performance is further enhanced by discriminating frequently confusing classes with support vector machines. The shake detection algorithm detects in real time the exact motion moment when the phone is shaken significantly by utilizing variance and mean of acceleration signals. The gesture interaction algorithms show reliable performance for commercialization; with 100 novice users, the average recognition rate was 96.9% on 11 gestures (digits 1-9, O, X) and users' movements were detected in real time. We have applied the motion understanding technologies to Samsung cell phones in Korean, American, Chinese and European markets since May 2005.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.564-572
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• 2002

This article describes the ultrasonic range sensor for the recognition of the Indoor environment, especially utilizing the multiple reflection properties of the sonar usually ignored as disturbances or noises. In this paper, we endow the ultrasonic range sensor with the active motion using the stepping servomechanism in order to get the multiple reflections with environment objects. Environment features such as target type, distance and azimuth based on the scanned one frame data of that multiple reflection patterns are recognized simultaneously.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.982-990
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• 2018

In recent years, many wearable devices and mobile apps related to life care have been developed, and a service for measuring the movement during walking and showing the amount of exercise has been provided. However, they do not measure walking in detail, so there may be errors in the total calorie consumption. If the user's behavior is measured by a multi-axis sensor and learned by a machine learning algorithm to recognize the kind of behavior, the detailed operation of walking can be autonomously distinguished and the total calorie consumption can be calculated more than the conventional method. In order to verify this, we measured activities and created a model using a machine learning algorithm. As a result of the comparison experiment, it was confirmed that the average accuracy was 12.5% or more higher than that of the conventional method. Also, in the measurement of the momentum, the calorie consumption accuracy is more than 49.53% than that of the conventional method. If the activity recognition is performed using the wearable device and the machine learning algorithm, the accuracy can be improved and the energy consumption calculation accuracy can be improved.

• Smart Media Journal
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• v.8 no.1
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• pp.51-58
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• 2019

This paper describes a gesture application to controlling the special effects of physical devices for 4D contents using the PWM (Pulse Width Modulation) method. The user operation recognized by the infrared sensor is interpreted as a command for 3D content control, several of which manipulate the device that generates the special effect to display the physical stimulus to the user. With the content controlled under the NUI (Natural User Interface) technique, the user can be directly put into an immersion experience, which leads to provision of the higher degree of interest and attention. In order to measure the efficiency of the proposed method, we implemented a PWM-based real-time linear control system that manages the parameters of the motion recognition and animation controller using the infrared sensor and transmits the event.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.91-92
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• 2024

본 논문에서는 키넥트 센서 기반으로 하는 동작 인식 애플리케이션을 설계하고 구현 한다. 이 애플리케이션은 본인이 응원하는 특정 연예인의 영상을 보고, 응원하는 동작을 하면 점수를 취득하게 되고, 누적되는 점수에 따라 그 연예인에 대한 기여도를 알 수 있도록 구현한다. 프레임별 조인트 움직임의 차이를 구하여 사용자의 움직임에 따른 점수를 부여하는 기능을 구현한다. 또한 전체 랭킹 시스템을 통해 동일한 연예인을 응원하는 사용자들이 공동의 소속감을 가지고, 더 나아가 자신들이 응원하는 연예인의 순위를 올리기 위한 경쟁을 유도하는 기능을 구현한다. 점수가 누적되면 단계별로 추가적인 애니메이션을 제공하여 흥미있게 볼 수 있는 기능도 구현한다.

• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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• pp.551-556
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• 2012

Objective: This study presents the effect of visual feedback on one-hand gesture performance in vision-based gesture recognition system when people use gestures to control a screen device remotely. Backgroud: gesture interaction receives growing attention because it uses advanced sensor technology and it allows users natural interaction using their own body motion. In generating motion, visual feedback has been to considered critical factor affect speed and accuracy. Method: three types of visual feedback(arrow, star, and animation) were selected and 20 gestures were listed. 12 participants perform each 20 gestures while given 3 types of visual feedback in turn. Results: People made longer hand trace and take longer time to make a gesture when they were given arrow shape feedback than star-shape feedback. The animation type feedback was most preferred. Conclusion: The type of visual feedback showed statistically significant effect on the length of hand trace, elapsed time, and speed of motion in performing a gesture. Application: This study could be applied to any device that needs visual feedback for device control. A big feedback generate shorter length of motion trace, less time, faster than smaller one when people performs gestures to control a device. So the big size of visual feedback would be recommended for a situation requiring fast actions. On the other hand, the smaller visual feedback would be recommended for a situation requiring elaborated actions.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.89-96
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• 2015

IT is widely used for biomechanics and AHRS sensor also be highlighted with small sized characteristics and price competitiveness in the field of motion measurement and analysis of sports. In this paper, we attach the AHRS to the figure skate shoes to measure the motion data like spin, forward/backward, jump, in/out edge and toe movement. In order to reduce the measurement error, we have adopted the sensors equipped with Madgwick complementary filtering and also use Euler angle to quaternion conversion to reduce the Gimbal-lock effect. We test and experiment the accuracy and execution time of the pattern recognition algorithms like PCA, ICA, LDA, SVM to show the recognition possibility of it on the basic motions of figure skating from the 9-axis trajectory information which is gathered from AHRS sensor. From the result, PCA, ICA have low accuracy, but LDA, SVM have good accuracy to use for recognition of basic motions of figure skating.