• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2524-2532
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• 1999

In this paper, we present a new buffer pool management scheme designed for video type news objects to build a cost-effective News On Demand storage server for serving users requests beyond the limitation of disk bandwidth. In a News On Demand Server where many of users request for video type news objects have to be serviced keeping their playback deadline, the maximum numbers of concurrent users are limited by the maximum disk bandwidth the server provides. With our proposed buffer cache management scheme, a requested data is checked to see whether or not it is worthy of caching by checking its average arrival interval and current disk traffic density. Subsequently, only granted news objects are permitted to get into the buffer pool, where buffer allocation is made not on the block basis but on the object basis. We evaluated the performance of our proposed caching algorithm through simulation. As a result of the simulation, we show that by using this caching scheme to support users requests for real time news data, compared with serving those requests only by disks, 30% of extra requests are served without additional cost increase.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.59-68
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• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.10-21
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• 2022

In order to improve formal presentation attitudes such as presentation of job interviews and presentation of project results at the company, there are few automated methods other than observation by colleagues or professors. In previous studies, it was reported that the speaker's stable speech and gaze processing affect the delivery power in the presentation. Also, there are studies that show that proper feedback on one's presentation has the effect of increasing the presenter's ability to present. In this paper, considering the positive aspects of correction, we developed a program that intelligently corrects the wrong presentation habits and attitudes of college students through facial analysis of videos and analyzed the proposed program's performance. The proposed program was developed through web-based verification of the use of redundant words and facial recognition and textualization of the presentation contents. To this end, an artificial intelligence model for classification was developed, and after extracting the video object, facial feature points were recognized based on the coordinates. Then, using 4000 facial data, the performance of the algorithm in this paper was compared and analyzed with the case of facial recognition using a Teachable Machine. Use the program to help presenters by correcting their presentation attitude.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.85-92
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• 2023

In this paper, we propose a method for automatically generating story-based abbreviated summaries from long-form dramas and movies. From the shooting stage, the basic premise was to compose a frame with illusion of depth considering the golden division as well as focus on the object of interest to focus the viewer's attention in terms of content delivery. To consider how to extract the appropriate frames for this purpose, we utilized elemental techniques that have been utilized in previous work on scene and shot detection, as well as work on identifying focus-related blur. After converting the videos shared on YouTube to frame-by-frame, we divided them into a entire frame and three partial regions for feature extraction, and calculated the results of applying Laplacian operator and FFT to each region to choose the FFT with relative consistency and robustness. By comparing the calculated values for the entire frame with the calculated values for the three regions, the target frames were selected based on the condition that relatively sharp regions could be identified. Based on the selected results, the final frames were extracted by combining the results of an offline change point detection method to ensure the continuity of the frames within the shot, and an edit decision list was constructed to produce an abbreviated summary of 62.77% of the footage with F1-Score of 75.9%

• KIPS Transactions on Software and Data Engineering
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• v.11 no.6
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• pp.255-266
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• 2022

The quality control of coarse aggregate among aggregates, which are the main ingredients of concrete, is currently carried out by SPC(Statistical Process Control) method through sampling. We construct a smart factory for manufacturing innovation by changing the quality control of coarse aggregates to inspect the coarse aggregates based on this image by acquired images through the camera instead of the current sieve analysis. First, obtained images were preprocessed, and HED(Hollistically-nested Edge Detection) which is the filter learned by deep learning segment each object. After analyzing each aggregate by image processing the segmentation result, fineness modulus and the aggregate shape rate are determined by analyzing result. The quality of aggregate obtained through the video was examined by calculate fineness modulus and aggregate shape rate and the accuracy of the algorithm was more than 90% accurate compared to that of aggregates through the sieve analysis. Furthermore, the aggregate shape rate could not be examined by conventional methods, but the content of this paper also allowed the measurement of the aggregate shape rate. For the aggregate shape rate, it was verified with the length of models, which showed a difference of ±4.5%. In the case of measuring the length of the aggregate, the algorithm result and actual length of the aggregate showed a ±6% difference. Analyzing the actual three-dimensional data in a two-dimensional video made a difference from the actual data, which requires further research.

• Journal of Internet Computing and Services
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• v.3 no.1
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• pp.81-90
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• 2002

Large-scale distributed applications based on Internet and client/server applications have to deal with series of problems. Load balancing, unpredictable communication delays, and networking failures can be the example of the series of problems. Therefore. sophisticated applications such as teleconferencing, video-on-demand, and concurrent software engineering require an abstracted group communication, CORBA does not address these paradigms adequately. It mainly deals with point-to-point communication and does not support the development of reliable applications that include predictable behavior in distributed systems. In this paper, we present our design, implementation and performance analysis of the group communication using the CORBA-ORB. JAVA-RML and Socket based on distributed computing Performance analysis will be estimated latency-lime according to object increment, in case of group communication using ORB of CORBA the average is 14.5172msec, in case of group communication using RMI of Java the average is 21.4085msec, in case of group communication using socket the average is becoming 18.0714msec. Each group communication using multicast and UDP can be estimated 0.2735msec and 0.2157msec. The performance of the CORBA-ORB group communication is increased because of the increased object by the result of this research. This study can be applied to the fault-tolerant client/server system, group-ware. text retrieval system, and financial information systems.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.137-143
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• 2014

Recently, as new paradigm for government operation called government 3.0, government is actively operating policy opening and sharing public data. In addition, the Ministry of Land are operating an open platform integrated map service (the VWorld) which provides a variety of video contents such as the country's national spatial information, traffic information and three-dimensional building for the public. According to W3C Foundation's Open Data Status Report(2013), our country has the evaluated results that the part of the government's policy support and planning is good while the part of the data management is vulnerable. So our country needs the quality improvement for the data management. In addition, a digital aerial photograph image data is required to be up-to-date for the three-dimensional spatial object data. In this paper, we present the method for enhancement of the accuracy of vertical position and for maintainment of up-to-date vertical position. Our methods evaluate the data quality and analyze the cause of error of measurement utilizing the national standard quality assessment method. The result of research shows that the accuracy of vertical position is improved if the height of the building captain is adjusted by the quality assessment values and a three-dimensional model has up-to-date data if reconstruction and extension information of construction register is utilized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.165-167
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• 2022

The proportion of cat cats among companion animals has been increasing at an average annual rate of 25.4% since 2012. Cats have strong wildness compared to dogs, so they have a characteristic of hiding diseases well. Therefore, when the guardian finds out that the cat has a disease, the disease may have already worsened. Symptoms such as anorexia (eating avoidance), vomiting, diarrhea, polydipsia, and polyuria in cats are some of the symptoms that appear in cat diseases such as diabetes, hyperthyroidism, renal failure, and panleukopenia. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia (drinking a lot of water), polyuria (a large amount of urine), and frequent urination (urinating frequently) more quickly. In this paper, 1) Efficient version of DeepLabCut for posture prediction running on an artificial intelligence server, 2) yolov4 for object detection, and 3) LSTM are used for behavior prediction. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the main server system.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.44-55
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• 2022

In order to automatically provide information on fruits in agricultural related broadcasting contents, instance image segmentation of target fruits is required. In addition, the information on the 3D pose of the corresponding fruit may be meaningfully used. This paper represents research that provides information about tomatoes in video content. A large amount of data is required to learn the instance segmentation, but it is difficult to obtain sufficient training data. Therefore, the training data is generated through a data augmentation technique based on a small amount of real images. Compared to the result using only the real images, it is shown that the detection performance is improved as a result of learning through the synthesized image created by separating the foreground and background. As a result of learning augmented images using images created using conventional image pre-processing techniques, it was shown that higher performance was obtained than synthetic images in which foreground and background were separated. To estimate the pose from the result of object detection, a point cloud was obtained using an RGB-D camera. Then, cylinder fitting based on least square minimization is performed, and the tomato pose is estimated through the axial direction of the cylinder. We show that the results of detection, instance image segmentation, and cylinder fitting of a target object effectively through various experiments.

• Cartoon and Animation Studies
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• s.50
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• pp.43-73
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• 2018

This is a study on 'Objet' in animation culture art education. Research on the use of Objet in modern art is actively under way. From Cubism to Dadaism, Surrealism, Futurism and Pop art, it is no exaggeration to say that the Objet is stepping with modern art. In addition, Objet has a remarkable value in the field of visual arts expressing 'motion' such as kinetic art, video art, media art, and animation. However, there are not many cases of classifying and studying the types of Objets used in artworks. Therefore, this researcher has been influenced by the surrealism discourse and prepared six types of Objets type analysis framework. And the research focused on 'the aesthetic emotion and educational aspect of creativity improvement' of Objet animation was conducted. The type analysis framework is named as a drawing Objet, Objet of existence, a morphine Objet, epidermis Objet, assigned Objet and assemblage Objet and this type is presented and analyzed with case image. The data used in this study was focused on the outcome of Objet animation that were trained for non-experts in culture and arts education. This aesthetic emotion refers to Freud's desire for life (Eros) as Attraction, and desire for death (Thanatos) as Uncanny (fearful unfamiliarity) and explains the conflicting concept with the Animism, the indigenous religion. Next, educational aspects of Objet animation creativity improvement in relation to the term 'functional fixedness' was discussed as described by Gestalt psychologist Karl Duncker (1903-1940). Overcoming the functional fixedness is a phenomenon that is fixed only to the functional aspects of things and can't be changed. In this study, the educational aspect of creativity improvement was demonstrated as a case of overcoming the functional fixedness through 'Objet Animation' culture and art education. Ultimately, this study is to prove the aesthetic emotion and creativity of the Objet animation by analyzing Objet types. Furthermore, it is meaningful to suggest direction when using 'Objet Animation' in culture and arts education.