• The Journal of Korean Physical Therapy
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• v.16 no.2
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• pp.156-168
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• 2004

Unilateral neglect is a common behavioral syndrome in patients following stroke. Unilateral neglect is characterized by the failure to report or responds to people or object presented to the side opposite a brain lesion. The patients with unilateral neglect are severely disabled in all daily activities, have a poor rehabilitation outcome and therefore require professional assessment and treatment This article reviews recent efficacy of rehabilitation techniques includings; drug, cueing, scanning training, prism lense, eye patching, trunk rotation, neck vibration, TENS, limb activation, video feedback. The purpose of this reviews are: to clarify the different types of neglect, as a basis for understanding the tests and measures of unilateral neglect and give information about recent treatments.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.7 no.1
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• pp.43-49
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• 1996

In this study, remote articulation training system which connects the hearing disabled trainee and the speech therapist via B-ISDN is introduced. The hearing disabled does not have the hearing feedback of his own pronuciation, and the chance of watching his speech organs movement trajectory will offer him the self-training of articulation. So the system has two purposes of self articulation training and trainer's on-line checking in remote place. We estimate the vocal tract articultory movements from the speech signal using inverse modelling and display the movement trajectoy on the sideview of human face graphically. The trajectories of trainees articulation is displayed along with the reference trajectories, so the trainee can control his articulating to make the two trajectories overlapped. For on-line communication and ckecking training record the system has the function of video conferencing and tranferring articulatory data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.11a
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• pp.181-186
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• 1997

Transcoding is the key technique to further reduce the bit-rate of a previously compressed video. The performance of the transcoding is evaluated by the two factors, the accuracy on the target bit-rate and the complexity of the implementation. In this paper, were propose a new rate control algorithm which has very accurate bit-rate control performance and much smaller computational complexity. For the accuracy problem, we empirically observe the relationship between the quantization step size and generated bits in requantization process and then find that the relationship can be characterized as the new piece-wise linear model. For the complexity problem, we reduce the role of feedback rate control. The simulation results show that the proposed method gives the better performance in the accuracy with the same picture quality than conventional rat control algorithm.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.4
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• pp.444-449
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• 2010

The PID control to the monitor color correction was applied. Converted Gamma LUT was applied to the video card. Color and brightness information from the PID controller was used as control inputs. Color and brightness information from a calibrated monitor is measured again. Then, the difference between the preset values for the PID controller was compensated by the feedback. The software measured by color meter was used for color and brightness information. All of the monitor does not measure the color and brightness was measured by sampling. The color and brightness from the monitor were measured not by complete enumeration but by sampling. In the experiment, the original image was displayed on the same monitor as well as two other brands, and then, Gamma and Contrast were measured and compared.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1112-1115
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• 2019

최근 딥러닝의 급격한 발전에 따라, 다양한 영상처리에 기반한 새로운 어플리케이션과 서비스가 개발되어지고 있다. 이러한 다양한 서비스들이 동작되는 플랫폼이 다양하고, 리소스에 제약이 많은 경우가 있어 일반적으로 이러한 딥러닝 기반 영상처리 서비스에서는 클라우드를 이용한 백엔드 서비스를 이용하는 경우가 많다. 그러나, 알고리즘 개발단계에서는 클라우드 백엔드 서비스가 적절하지만, 실제로 제품 및 서비스의 필드 적용에 있어서는 클라우드 사용에 따른 제약이 상당한 걸림돌로 작용한다. 그리하여 본 논문에서는 다양한 디바이스의 영상 데이터를 로컬 또는 기관에 있는 충분한 자원 활용이 가능한 서버로 전송하여 프로세싱 후 실시간 결과를 feedback받을 수 있는 효율적인 back-end 딥러닝 영상분석 서비스 프레임워크를 제안한다.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.230-237
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• 2022

A technology that allows users to feel the elasticity of fabric through force feedback in the fashion and textile fields is very helpful to related manufacturing and sales areas. Currently bundle of fabrics, so called Swatch, is the only available way for the designer, manufacturer and the end-user to feel the fabrics. Images and video clips provide only visual characteristics, hence touch and stiffness are also very important characteristics to check beforehand. A study is conducted on a haptic device, which estimates the amount of change in the length of the virtual fabric and generates resistive force so that the user could feel the fabric stiffness. Since cables that can only transmit the tensile force are used, a force realization method is proposed, and it is verified numerically and experimentally.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.261-282
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• 2024

This study proposed and evaluated electroencephalography (EEG)-based and eye-tracking-based methods to determine relevance by utilizing users' implicit relevance feedback while navigating content in a digital library. For this, EEG/eye-tracking experiments were conducted on 32 participants using video, image, and text data. To assess the usefulness of the proposed methods, deep learning-based artificial intelligence (AI) techniques were used as a competitive benchmark. The evaluation results showed that EEG component-based methods (av_P600 and f_P3b components) demonstrated high classification accuracy in selecting relevant videos and images (faces/emotions). In contrast, AI-based methods, specifically object recognition and natural language processing, showed high classification accuracy for selecting images (objects) and texts (newspaper articles). Finally, guidelines for implementing a digital library interface based on EEG, eye-tracking, and artificial intelligence technologies have been proposed. Specifically, a system model based on implicit relevance feedback has been presented. Moreover, to enhance classification accuracy, methods suitable for each media type have been suggested, including EEG-based, eye-tracking-based, and AI-based approaches.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10A
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• pp.886-895
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• 2005

As the networked media technology have been grown in recent, there have been many research works to deliver high-quality video such as HDV and HDTV over the Internet. To realize high-quality media service over the Internet, however, the network adaptive streaming scheme is required to adopt to the dynamic fluctuation of underlying networks. In this paper, we design and implement the network-adaptive HD(high definition) MPEG-2 streaming system employing the frame-based prioritized packetization. Delivered video is inputted from the JVC HDV camera to the streaming sewer in real-time. It has a bit-rate of 19.2 Mbps and is multiplexed to the MPEG-2 TS (MPEG-2 MP@HL). For the monitoring of network status, the packet loss rate and the average jitter are measured by using parsing of RTP packet header in the streaming client and they are sent to the streaming server periodically The network adaptation manager in the streaming server estimates the current network status from feedback packets and adaptively adjusts the sending rate by frame dropping. For this, we propose the real-time parsing and the frame-based prioritized packetization of the TS packet. The proposed system is implemented in software and evaluated over the LAN testbed. The experimental results show that the proposed system can enhance the end-to-end QoS of HD video streaming over the best-effort network.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.112-118
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• 2009

Skin color segmentation techniques have been widely utilized for face/hand detection and tracking in many applications such as a diagnosis system using facial information, human-robot interaction, an image retrieval system. In case of a video image, it is common that the skin color model for a target is updated every frame for the robust target tracking against illumination change. As for a single image, however, most of studies employ a fixed skin color model which may result in low detection rate or high false positive errors. In this paper, we propose a novel method for effective skin color segmentation in a single image, which modifies the conditions for skin color segmentation iteratively by the image feedback of segmented skin color region in a given image.

• Journal of the Korean School Mathematics Society
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• v.10 no.2
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• pp.263-288
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• 2007

The purpose of this study is to search the effective teaching-learning program by considering how affect on formation of the process-object perspective of linear function using Excel. In this study we analyzed function units in textbook and examined how Excel affect on the formation of the process-object perspective of linear function. Teaching experiment was based on qualitative case study and performed for five classes with five 8th graders. Data were gathered through observations, audio-taped interviews, video recording of the students 'work, students' worksheets, and detailed field notes. Findings indicate that exploration learning environment using Excel could supplement paper-and-pencil environment. We found that intuitive, dynamic, explorative, feedback skills via Excel can play the role of scaffolding supporting formation of process perspective object perspective of linear function.