• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1225-1235
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• 2016

This paper presents a method for computer-assisted slide presentation using vision-based gesture recognition. The proposed method consists of a sequence of steps, first detecting a hand in the scene of projector beam, then estimating the smooth trajectory of a hand or a pointing finger using Kalman Filter, and finally interfacing to an application system. Additional slide navigation control includes moving back and forth the pages of the presentation. The proposed method is to help speakers for an effective presentation with natural improved interaction with the computer. In particular, the proposed method of using finger pointing is believed to be more effective than using a laser pointer since the hand, the pointing or finger are more visible and thus can better grab the attention of the audience.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.199-204
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• 2013

An implementation method of real-time numeral recognizer based on gesture is presented in this paper for various information devices. The proposed algorithm steadily captures the motion of a hand on 3D open space with the Kinect sensor. The captured hand motion is simplified with PCA, in order to preserve the trace consistency and to minimize the trace variations due to noises and size changes. In addition, we also propose a new HMM using both the gradient and the positional features of the simplified hand stroke. As the result, the proposed algorithm has robust characteristics to the variations of the size and speed of hand motion. The recognition rate is increased up to 30%, because of this combined model. Experimental results showed that the proposed algorithm gives a high recognition rate about 98%.

• Smart Media Journal
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• v.1 no.2
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• pp.40-46
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• 2012

In this paper, we describe interactive contents which is used the result of the inputted interface recognizing vision-based body gesture. Because the content uses the imp which is the common culture as the subject in Asia, we can enjoy it with culture familiarity. And also since the player can use their own gesture to fight with the imp in the game, they are naturally absorbed in the game. And the users can choose the multiple endings of the contents in the end of the scenario. In the part of the gesture recognition, KINECT is used to obtain the three-dimensional coordinates of each joint of the limb to capture the static pose of the actions. The vision-based 3D human pose recognition technology is used to method for convey human gesture in HCI(Human-Computer Interaction). 2D pose model based recognition method recognizes simple 2D human pose in particular environment On the other hand, 3D pose model which describes 3D human body skeletal structure can recognize more complex 3D pose than 2D pose model in because it can use joint angle and shape information of body part Because gestures can be presented through sequential static poses, we recognize the gestures which are configured poses by using HMM In this paper, we describe the interactive content which is used as input interface by using gesture recognition result. So, we can control the contents using only user's gestures naturally. And we intended to improve the immersion and the interest by using the imp who is used real-time interaction with user.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.481-486
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• 2011

Recently, most presentations have been presented on the screen using the computer. This paper suggests that the computer can be controlled by the gesturing recognition, without the help of any person or tools. If we use only information in the form of images, we should have a high-resolution camera for capturing the images and a computer that can treat high-resolution images. However, this paper will present a solution whereby a low-resolution camera can be used at the stage. It uses the supersonic sensor to trace the presenter's location and a low-resolution camera for capturing the necessary limited and small area. The gesture is defined by the number of fingers and one's hand positions which are recognized by the Erosion / Dilation and Subtraction algorithm. The system this paper addresses has improved 13%, when comparing tests between the image-only data system and this paper's system. The gesture recognition tests have a 98% success rate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.91-97
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• 2013

A finger-gesture remote controller using the single camera is implemented in this paper, which is base on the recognition of finger number and finger moving direction. Proposed method uses the transformed YCbCr color-difference information to extract the hand region effectively. The number and position of finger are computer by using a double circle tracing method. Specially, a user continuous-command can be performed repeatedly by recognizing the finger-gesture direction of single shape. The position information of finger enables a user command to amplify a same command in the User eXperience. Also, all processing tasks are implemented by using the Intel OpenCV library and C++ language. In order to evaluate the performance of the our proposed method, after applying to the commercial video player software as a remote controller. As a result, the proposed method showed the average 89% recognition ratio by the user command-mode.

• Smart Media Journal
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• v.4 no.1
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• pp.33-38
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• 2015

In this paper, we propose the methods not only to eliminate ELF(Extremely Low Frequency) EMI(Electro-Magnetic Interference) noice for extending recognition distance, but also to utilize the the PLN for detecting starting instance of a hand gesture using electric potential sensor. First, we measure strength of electric field generated in the smart devices such as TV and phone, and minimize EMI through efficient arrangement of the sensors. Meanwhile, we utilize the 60 Hz PLN to extract the starting point of hand gesture. Thereafter, we eliminate the PLN generated in the smart device and circuit of sensors. And then, we shield the sensors from an electric noise generated from devices. Finally, through analyzing the frequency components according to the gesture of target, we use the low pass filter and the Kalman filter for elimination of remaining electric noise. We analyze and evaluate the proposed ELF-band EMI eliminating method for non-contact remote sensing of the EPS(Electric Potential Sensor). Combined with a detecting technique of gesture starting point, the recognition distance for gestures has been proven to be extended to more than 3m, which is critical for real application.

• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.501-507
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• 2012

Human body motion is a non-verbal part for interaction or movement that can be used to involves real world and virtual world. In this paper, we explain a study on natural user interface (NUI) in human hand motion recognition using RGB color information and depth information by Kinect camera from Microsoft Corporation. To achieve the goal, hand tracking and gesture recognition have no major dependencies of the work environment, lighting or users' skin color, libraries of particular use for natural interaction and Kinect device, which serves to provide RGB images of the environment and the depth map of the scene were used. An improved Camshift tracking algorithm is used to tracking hand motion, the experimental results show out it has better performance than Camshift algorithm, and it has higher stability and accuracy as well.

• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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• pp.585-591
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• 2012

Objective: The aim of this study is to propose the contactless gesture-based interface on smart mobile devices for especially rhythm action games. Background: Most existing approaches about interactions of smart mobile games are tab on the touch screen. However that way is such undesirable for someone or for sometimes, because of the disabled person, or the inconvenience that users need to touch/tab specific devices. Moreover more importantly, new interaction can derive new possibilities from stranded game genre. Method: In this paper, I present a smart mobile game with contactless gesture-based interaction and the interfaces using computer vision technology. Discovering the gestures which are easy to recognize and research of interaction system that fits to game on smart mobile device are conducted as previous studies. A combination between augmented reality technique and contactless gesture interaction is also tried. Results: The rhythm game allows a user to interact with smart mobile devices using hand gestures, without touching or tabbing the screen. Moreover users can feel fun in the game as other games. Conclusion: Evaluation results show that users make low failure numbers, and the game is able to recognize gestures with quite high precision in real time. Therefore the contactless gesture-based interaction has potentials to smart mobile game. Application: The results are applied to the commercial game application.

• Smart Media Journal
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• v.5 no.3
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• pp.35-41
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• 2016

In this paper, we propose hand-gesture signal recognition based on EPS(Electronic Potential Sensor) using Deep learning model. Extracted signals which from Electronic field based sensor, EPS have much of the noise, so it must remove in pre-processing. After the noise are removed with filter using frequency feature, the signals are reconstructed with dimensional transformation to overcome limit which have just one-dimension feature with voltage value for using convolution operation. Then, the reconstructed signal data is finally classified and recognized using multiple learning layers model based on deep learning. Since the statistical model based on probability is sensitive to initial parameters, the result can change after training in modeling phase. Deep learning model can overcome this problem because of several layers in training phase. In experiment, we used two different deep learning structures, Convolutional neural networks and Recurrent Neural Network and compared with statistical model algorithm with four kinds of gestures. The recognition result of method using convolutional neural network is better than other algorithms in EPS gesture signal recognition.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.223-224
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• 2010

본 논문에서는 형상 분해(Shape Decomposition)를 이용한 손동작 인식 방법을 제안한다. 형상 분해 방법을 손동작 인식에 적용함으로써 다양한 동작에 대해서 유연한 인식이 가능하며, 기존의 형상 분해 방법을 손 형상 분해에 적합하게 효율적으로 개선함으로써 실시간 연산이 가능하도록 하였다.