• International journal of advanced smart convergence
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• v.10 no.4
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• pp.110-116
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• 2021

This paper proposed a real-time earlobe detection system using deep learning on the web. Existing deep learning-based detection methods often find independent objects such as cars, mugs, cats, and people. We proposed a way to receive an image through the camera of the user device in a web environment and detect the earlobe on the server. First, we took a picture of the user's face with the user's device camera on the web so that the user's ears were visible. After that, we sent the photographed user's face to the server to find the earlobe. Based on the detected results, we printed an earring model on the user's earlobe on the web. We trained an existing YOLO v5 model using a dataset of about 200 that created a bounding box on the earlobe. We estimated the position of the earlobe through a trained deep learning model. Through this process, we proposed a real-time earlobe detection system on the web. The proposed method showed the performance of detecting earlobes in real-time and loading 3D models from the web in real-time.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.198-205
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• 2022

Along with a variety of coding education, physical computing education for controlling various sensors is being actively conducted for elementary, middle, and high school students in line with the era of the fourth industrial revolution. A problem with physical computing education using Arduino is pin connection errors between Arduino and various sensors. Most of the students who come into contact with the Arduino for the first time often do not know the purpose of the Arduino pin and the connection position of the pin. Also, hardware built with incorrect pin connections to the Arduino board often does not work properly. If this case continues, students will lose interest in coding education. Therefore, in this paper, we implemented an augmented reality application that informs the connection process of the Arduino board and the sensor during physical computing coding education using Arduino, and designed and implemented educational content for the Arduino pin position and connection process. First, we explain the role of the Arduino board and the sensor and the location of the pins. After that, the students run the educational augmented reality educational content using their smartphones and check the correct pin connection process between the Arduino and the sensor. In the physical computing education, augmented reality content is used to increase the understanding and immersion of the class. It is expected that the educational effect will also increase by inducing fun and interest in physical computing coding education.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.64-79
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• 2022

The concept of Virtual Character has been developed for a long time with people's demand for cultural and entertainment products such as games, animations, and movies. In recent years, with the rapid development of concepts and industries such as social media, self-media, web3.0, artificial intelligence, virtual reality, and Metaverse, Virtual Character has also expanded new derivative concepts such as Virtual Idol, Virtual YouTuber, and Virtual Digital Human. With the development of technology, people's life is gradually moving towards digitalization and virtualization. At the same time, under the global environment of the new crown epidemic, human social activities are rapidly developing in the direction of network society and online society. From the perspective of digital media content, this paper studies the production technology of Virtual Character related products in the Chinese market, and analyzes the future development direction and possibility of the Virtual Character industry in combination with new media development directions and technical production methods. Consider and provide reference for the development of combined applications of digital media content industry, Virtual Character and Metaverse industry.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.164-170
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• 2023

The purpose of this study is to analyze the big data of Adidas brand participating in the Qatar World Cup in 2022 as a FIFA partner to understand useful information, semantic connection and context from unstructured data. Therefore, this study collected big data generated during the World Cup from Adidas participating in sponsorship as a FIFA partner for the 2022 Qatar World Cup and collected data from major portal sites to understand its meaning. According to text mining analysis, 'Adidas' was used the most 3,340 times based on the frequency of keyword appearance, followed by 'World Cup', 'Qatar World Cup', 'Soccer', 'Lionel Messi', 'Qatar', 'FIFA', 'Korea', and 'Uniform'. In addition, the TF-IDF rankings were 'Qatar World Cup', 'Soccer', 'Lionel Messi', 'World Cup', 'Uniform', 'Qatar', 'FIFA', 'Ronaldo', 'Korea', and 'Nike'. As a result of semantic network analysis and CONCOR analysis, four groups were formed. First, Cluster A named it 'Qatar World Cup Sponsor' as words such as 'Adidas', 'Nike', 'Qatar World Cup', 'Sponsor', 'Sponsor Company', 'Marketing', 'Nation', 'Launch', 'Official', 'Commemoration' and 'National Team' were formed into groups. Second, B Cluster named it 'Group stage' as words such as 'Qatar', 'Uruguay', 'FIFA' and 'group stage' were formed into groups. Third, C Cluster named it 'Winning' as words such as 'World Cup Winning', 'Champion', 'France', 'Argentina', 'Lionel Messi', 'Advertising' and 'Photograph' formed a group. Fourth, D Cluster named it 'Official Ball' as words such as 'Official Ball', 'World Cup Official Ball', 'Soccer Ball', 'All Times', 'Al Rihla', 'Public', 'Technology' was formed into groups.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.130-135
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• 2024

The Stable diffsuion AI tool is popular among designers because of its flexible and powerful image generation capabilities. However, due to the diversity of its AI models, it needs to spend a lot of time testing different AI models in the face of different design plans, so choosing a suitable general AI model has become a big problem at present. In this paper, by comparing the AI images generated by two different Stable diffsuion models, the advantages and disadvantages of each model are analyzed from the aspects of the matching degree of the AI image and the prompt, the color composition and light composition of the image, and the general AI model that the generated AI image has an aesthetic sense is analyzed, and the designer does not need to take cumbersome steps. A satisfactory AI image can be obtained. The results show that Playground V2.5 model can be used as a general AI model, which has both aesthetic and design sense in various style design requirements. As a result, content designers can focus more on creative content development, and expect more groundbreaking technologies to merge generative AI with content design.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.36-42
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• 2016

Recently, many 3D contents have been produced through the multiview camera system. In this system, since a difference of the viewpoint between color and depth cameras is inevitable, the camera parameter plays the important role to adjust the viewpoint as a preprocessing step. The conventional camera calibration method is inconvenient to users since we need to choose pattern features manually after capturing a planar chessboard with various poses. Therefore, we propose a semi-auto camera calibration method using a circular sampling and an homography estimation. Firstly, The proposed method extracts the candidates of the pattern features from the images by FAST corner detector. Next, we reduce the amount of the candidates by the circular sampling and obtain the complete point cloud by the homography estimation. Lastly, we compute the accurate position having the sub-pixel accuracy of the pattern features by the approximation of the hyper parabola surface. We investigated which factor affects the result of the pattern feature detection at each step. Compared to the conventional method, we found the proposed method released the inconvenience of the manual operation but maintained the accuracy of the camera parameters.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.957-964
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• 2016

Acquisition of reliable depth maps is a critical requirement in many applications such as 3D videos and free-viewpoint TV. Depth information can be obtained from the object directly using physical sensors, such as infrared ray (IR) sensors. Recently, Time-of-Flight (ToF) range camera including KINECT depth camera became popular alternatives for dense depth sensing. Although ToF cameras can capture depth information for object in real time, but are noisy and subject to low resolutions. Recently, filter-based depth up-sampling algorithms such as joint bilateral upsampling (JBU) and noise-aware filter for depth up-sampling (NAFDU) have been proposed to get high quality depth information. However, these methods often lead to texture copying in the upsampled depth map. To overcome this limitation, we formulate a convex optimization problem using higher order regularization for depth map upsampling. We decrease the texture copying problem of the upsampled depth map by using edge weighting term that chosen by the edge information. Experimental results have shown that our scheme produced more reliable depth maps compared with previous methods.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.73-80
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• 2012

Recently, medical equipments are developed and used for diagnosis or studies. In addition, demand of techniques which automatically deal with three dimensional medical images obtained from the medical equipments is growing. One of the techniques is automatic bone segmentation which is expected to enhance the diagnosis efficiency of osteoporosis, fracture, and other bone diseases. Although various researches have been proposed to solve it, they are unable to be used in practice since a size of the medical data is large and there are many low contrast boundaries with other tissues. In this paper, we present a fast and accurate automatic framework for bone segmentation based on multi-resolutions. On a low resolution step, a position of the bone is roughly detected using constrained branch and mincut which find the optimal template from the training set. Then, the segmentation and the registration are iteratively conducted on the multiple resolutions. To evaluate the performance of the proposed method, we make an experiment with femur and tibia from 50 test knee magnetic resonance images using 100 training set. The proposed method outperformed the constrained branch and mincut in aspect of segmentation accuracy and implementation time.

• Proceedings of the Optical Society of Korea Conference
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• 2007.07a
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• pp.223-224
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• 2007

광기록의 역사는 1980년대초 Sony와 Philips가 공동 개발한 CD (compact disc: 640MB)의 출현으로부터 시작하여 1996년의 DVD (digital versatile disc: 4.7GB)를 거쳐 최근의 BD (Blu-ray disc: >20GB)에까지 이르고 있다. Read-only memory, recordable, rewritable 등 다양한 저장 및 재생방식이 존재하는데, 이는 레이저 조사에 의한 기록매체의 특성변화의 가역성 (reversibility)에 의존하므로 저장 및 재생방식에 따라 저장매체 또한 다르게 된다. 기록용량의 증가는 레이저의 파장이 짧아지고 동시에 사용된 렌즈의 개구수 (NA: Numerical aperture)가 증가함에 따른 빔 spot size의 감소에 기인한다. 회절한계를 극복하여 빔의 spot size를 줄이고자 하는 연구는 현재도 전세계적으로 활발히 이루어지고 있고 이러한 노력의 일환으로 어느 정도의 추가적인 저장용량 증가는 가능할 수 있으나, 2차원 방식으로는 대용량 광정보기록 (수백 GB ${\sim}$ TB급)의 실현은 불가능하다는 것이 일반적인 예상이다. 한편 장기적으로 기존의 2차원 정보기록방식을 대체하고 저장용량을 획기적으로 증가시킬 수 있는 bit-type 3차원 광정보기록의 개념이 1990년을 전.후로 처음으로 제시되었다. 이는 2차원 bit 정보가 수십 내지 수백 개의 다층 (multi-layer) 형태로 기록되는 방식인데, 그동안 산업체의 관심이 상대적으로 높지 않았던 이유는 영화, 음악 등 엔터테인먼트 시장성 확대를 위해 Blu-ray disc나 HD-DVD에 대한 연구개발에 치중해왔기 때문이다. 하지만 최근 급변하는 정보시스템 서비스 환경 속에서 정보유통량이 기하급수적으로 증가하고 있고 개인이 취급하는 정보량도 2010년경에는 수백 GB 단위가 될 것으로 예상되고 있으며 디지털 방송, 네트워크를 기반으로 한 서비스 수요 뿐 만 아니라 전자도서관이나 VOD (Video on Demand) 서비스 사업에 필수적인 수 TB급의 대용량 저장장치에 대한 수요 또한 크게 증가할 것으로 전망된다. 이에 따라 점차 그 물리적 한계에 다다르고 있는 기존의2차원 정보저장방식을 대체하고 저장용량을 획기적으로 증가시킬 수 있는3차원 정보기록(> $10^{13}$ $bits/cm^3$)에 대한 필요성이 대두된다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2010.04a
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• pp.151-153
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• 2010

In this paper, the tri-band planar monopole microstrip antenna which stimulaneously meets the three bands such as TRS, WLAN and DMB is designed. The designed antenna size was smaller using CPW-fed structure that shows a ground-plane and a patch-plane are existed at one layer. The proposed antenna is designed on FR-4 substrate with a relative dielectric constant 4.3, thickness of 1.5mm and tangent loss 0.04. The designed antenna shows that VSWR is below 2 and has good return loss below -10dB over the three bandwidths.