• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.15-20
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• 2019

As the machine learning research has developed, the field of translation and image analysis such as optical character recognition has made great progress. However, video translation that combines these two is slower than previous developments. In this paper, we develop an image translator that combines existing OCR technology and translation technology and verify its effectiveness. Before developing, we presented what functions are needed to implement this system and how to implement them, and then tested their performance. With the application program developed through this paper, users can access translation more conveniently, and also can contribute to ensuring the convenience provided in any environment.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.189-194
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• 2022

As non-face-to-face activities have become commonplace, online video conferencing platforms have become popular collaboration tools. However, existing video conferencing platforms have a structure in which one side unilaterally exchanges information, potentially increase the fatigue of meeting participants. In this study, we designed a video conferencing platform utilizing virtual reality (VR), a metaverse technology, to enable various interactions. A virtual conferencing space and realistic VR video conferencing content authoring tool support system were designed using Meta's Oculus Quest 2 hardware, the Unity engine, and 3D Max software. With the Photon software development kit, voice recognition was designed to perform automatic text translation with the Watson application programming interface, allowing the online video conferencing participants to communicate smoothly even if using different languages. It is expected that the proposed video conferencing platform will enable conference participants to interact and improve their work efficiency.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.193-200
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• 2019

Hearing impaired people are living in a voice culture area, but due to the difficulty of communicating with normal people using sign language, many people experience discomfort in daily life and social life and various disadvantages unlike their desires. Therefore, in this paper, we study a sign language translation system for communication between a normal person and a hearing impaired person using sign language and implement a prototype system for this. Previous studies on sign language translation systems for communication between normal people and hearing impaired people using sign language are classified into two types using video image system and shape input device. However, existing sign language translation systems have some problems that they do not recognize various sign language expressions of sign language users and require special devices. In this paper, we use machine learning method of artificial neural network to recognize various sign language expressions of sign language users. By using generalized smart phone and various video equipment for sign language image recognition, we intend to improve the usability of sign language translation system.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.185-192
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• 2019

In the case of a hearing impaired person using sign language, there are many difficulties in communicating with a normal person who does not understand sign language. The sign language translation system is a system that enables communication between the hearing impaired person using sign language and the normal person who does not understand sign language in this situation. Previous studies on sign language translation systems for communication between normal people and hearing impaired people using sign language are classified into two types using video image system and shape input device. However, the existing sign language translation system does not solve such difficulties due to some problems. Existing sign language translation systems have some problems that they do not recognize various sign language expressions of sign language users and require special devices. Therefore, in this paper, a sign language translation system using an artificial neural network is devised to overcome the problems of the existing system.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.25-35
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• 2021

We are able to watch international multimedia anytime and anywhere, if we have the devices to connect Internet. Netflix and Youtube are the most massive and the most visited streaming platforms in the world. So If audiences are not familiar with the exotic culture such as behaviors, contexts, sarcasm, history and the current issues, It would happen a consequence that they entirely have to rely on subtitles in order to get inform. This research hereby aims to compare Korean transcriptions of the same movies streamed by the two selected platforms(Netflix and Youtube). As a result, good translation is that translators should use appropriate omissions and detailed explanations in limited time and space so that audience can concentrate on the vedio. If translators study the work in depth and spend enough time working on it, the quality of translation will definitely increase. Finally, this study contributed to the revitalization of the video translation market, which is still in the past, through the misinterpretation of videos produced at a low unit price and with minimal time without guidelines for video translation.

• Electronics and Telecommunications Trends
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• v.35 no.4
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• pp.91-102
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• 2020

Recently, generative adversarial networks (GANs) is a field of research that has rapidly emerged wherein many studies conducted shows overwhelming results. Initially, this was at the level of imitating the training dataset. However, the GAN is currently useful in many fields, such as transformation of data categories, restoration of erased parts of images, copying facial expressions of humans, and creation of artworks depicting a dead painter's style. Although many outstanding research achievements have been attracting attention recently, GANs have encountered many challenges. First, they require a large memory facility for research. Second, there are still technical limitations in processing high-resolution images over 4K. Third, many GAN learning methods have a problem of instability in the training stage. However, recent research results show images that are difficult to distinguish whether they are real or fake, even with the naked eye, and the resolution of 4K and above is being developed. With the increase in image quality and resolution, many applications in the field of design and image and video editing are now available, including those that draw a photorealistic image as a simple sketch or easily modify unnecessary parts of an image or a video. In this paper, we discuss how GANs started, including the base architecture and latest technologies of GANs used in high-resolution, high-quality image creation, image and video editing, style translation, content transfer, and technology.

• ETRI Journal
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• v.23 no.4
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• pp.190-198
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• 2001

The performance of Motion Compensated Discrete Cosine Transform (MC-DCT) video coding is improved by using the region adaptive subband image coding [18]. On the assumption that the video is acquired from the camera on a moving platform and the distance between the camera and the scene is large enough, both the motion of camera and the motion of moving objects in a frame are compensated. For the compensation of camera motion, a feature matching algorithm is employed. Several feature points extracted using a Sobel operator are used to compensate the camera motion of translation, rotation, and zoom. The illumination change between frames is also compensated. Motion compensated frame differences are divided into three regions called stationary background, moving objects, and newly emerging areas each of which is arbitrarily shaped. Different quantizers are used for different regions. Compared to the conventional MC-DCT video coding using block matching algorithm, our video coding scheme shows about 1.0-dB improvements on average for the experimental video samples.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.140-147
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• 2024

In the Republic of Korea, people with hearing impairments are the second-largest demographic within the registered disability community, following those with physical disabilities. Despite this demographic significance, research on sign language translation technology is limited due to several reasons including the limited market size and the lack of adequately annotated datasets. Despite the difficulties, a few researchers continue to improve the performacne of sign language translation technologies by employing the recent advance of deep learning, for example, the transformer architecture, as the transformer-based models have demonstrated noteworthy performance in tasks such as action recognition and video classification. This study focuses on enhancing the recognition performance of sign language translation by combining transformers with 3D-CNN. Through experimental evaluations using the PHOENIX-Wether-2014T dataset [1], we show that the proposed model exhibits comparable performance to existing models in terms of Floating Point Operations Per Second (FLOPs).

• Journal of the Korean Chemical Society
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• v.54 no.4
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• pp.465-470
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• 2010

Using interesting video clips corresponding to lesson subjects for students who favour visual representation is one of the good methods to enhance students' preference for science class. There are many moving picture web sites to get video clips easily via internet and 'YouTube' is very popular and one of the largest reservoir. In this study, every student in the 'Chemistry I' class, which is a class for 11th grade, was requested to search a video clip corresponding to lesson subjects and to make a presentation in the class. After 1st semester, students' response about the class using YouTube was examined by survey. As a result, students preferred and were interested in the class using YouTube than class centered on textbook. And students preferred YouTube clips showing unusual experiments that were related with contents of subject. In addition, experiments and watching their real phenomena were an interesting factor and helpful factor of learning chemistry in YouTube video clips, respectively. However, translation of English used in the video clips seemed to be a difficult part for students.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.59-71
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• 1994

This paper proposes a motion estimation method in video sequences based on the feature based matching and anistropic propagation. It measures translation and rotation parameters using a relaxation scheme at feature points and object orinted anistropic propagation in continuous and discontinuous regions. Also an iterative improvement motion extimation based on the strongly coupled module fusion and adaptive smoothing is proposed. Computer simulation results show the effectiveness of the proposed algorithm.