• Journal of Fashion Business
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• v.24 no.1
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• pp.75-87
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• 2020

The purpose of this study is to find trends in new media fashion content by analyzing the fashion content of the official Instagram accounts of domestic fashion magazines that are being transformed by digital media. The framework for these analysis of fashion content type and methods of production is based on one used in an earlier research project. Empirical analysis is conducted on Vogue Korea's official Instagram accounts, using the highest number of major views as the secondary measure of interest. After screening for fashion content in posts on the Vogue Korea account for four months, 291 short video postings were extracted to analyze the number of views the postings received. The results were categorized as 'star', 'show/exhibition', 'product', 'shop', 'fashion film', 'designer', or 'event', included in the data are the number of postings by type and the number of views by post. Based on the characteristics of the creator and the editing, the posts were classified into 'professional production highlight', 'professional production private', 'UCC' or 'GIF' videos, the number of views per post were also collected. The research results show different levels of interest depending on the type of fashion content, and also on the way the videos were produced. The study also investigated how the combination of these two factors affects interest. When producing a new media fashion content, combining a 'star' type post with 'professional production private' video content was most popular. The selection of production method is therefore important even given the same type of content.

• Child Health Nursing Research
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• v.24 no.2
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• pp.208-219
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• 2018

Purpose: The purpose of this study was to explore nursing students' experiences of debriefing after simulation-based learning and to obtain fundamental data to support the development of effective teaching strategies. Methods: Sixty-seven nursing students participated in this study from April to May, 2017. This was a descriptive study analyzing the content of students' descriptions of structured questions in 3 stages (description, analysis, and application) based on recorded videos. Results: The description stage was classified into 3 categories for problem recognition, 4 categories for the nursing plan, and 6 categories for the nursing intervention. The analysis stage was classified into 6 categories for satisfactory practice, 3 categories for experience and 4 categories for what they learned through practice. The application stage was classified into 5 categories, that were to be mastered, and 6 categories, that were important to recognize. Conclusion: This study succeeded in charaterizing learners' experiences of debriefing. During the debriefing, students watched recorded videos, and we found that self-evaluation through structured questionnaires could be a very effective way to strengthen students' core competencies. Our content analysis of the debriefing is expected to contribute to the development of effective strategies in simulation-based education for students and nurses.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.89-98
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• 2007

For browsing, searching, and manipulating video documents, an indexing technique to describe video contents is required. Until now, the indexing process is mostly carried out by specialists who manually assign a few keywords to the video contents and thereby this work becomes an expensive and time consuming task. Therefore, automatic classification of video content is necessary. We propose a fully automatic and computationally efficient method for analysis and summarization of spots news video for 5 spots news video such as soccer, golf, baseball, basketball and volleyball. First of all, spots news videos are classified as anchor-person Shots, and the other shots are classified as news reports shots. Shot classification is based on image preprocessing and color features of the anchor-person shots. We then use the dominant color of the field and motion features for analysis of sports shots, Finally, sports shots are classified into five genre type. We achieved an overall average classification accuracy of 75% on sports news videos with 241 scenes. Therefore, the proposed method can be further used to search news video for individual sports news and sports highlights.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1A
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• pp.51-56
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• 2012

In order to reduce the complexity of HEVC, we propose a fast mode decision algorithm in depth videos. Since almost CU mode is decided as SKIP mode in depth-continuity regions, we design the algorithm using the property of depth videos. If cost of SKIP is smaller than the multiplication between the threshold for EarlySKIP and average cost of SKIP, EarlySKIP is performed. Otherwise, we calculate Inter $2N{\times}2N$. Then, if motion vector of Inter $2N{\times}2N$ is 0 and variance of CU is smaller than threshold for inter, we skip Inter $2N{\times}N$, Inter $N{\times}2N$. Experimental results show that our proposed algorithm reduces the encoding time from 39% to 82% with negligible PSNR loss and bitrate increase.

• Journal of Internet Computing and Services
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• v.5 no.1
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• pp.15-23
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• 2004

This paper presents distributive web-caching technique on the Head-End-Network (HNET) to solve excessive load of multimedia sever and inefficient use of network resources, The proposed web-caching is not concentration of load for a specific Head-End-Node(HEN), and it has advantage that there is no copy of a specific item on distributive HENs. This technique distributively stores on HENs partial streams of requested videos from clients connected to HENs and the order of store streams follows the order of request of identical video items from HENs. Thus, storing streams on each HEN that requests sevice are different. When a client requests the cached video on some HENs, the HEN that connects him receives streams in the order of store from HENs which stored them and it transmits them to him. These procedures are performed under the control of SA. This technique uses cache replacement algorithm that the combination of LFU, LRU and the last remove for the first stream of videos In order to reduce end-to-end delay.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3018-3038
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• 2020

In the stereoscopic or multiview display, the depth video illustrates visual distances between objects and camera. To promote the computational efficiency of depth video encoder, we exploit the intra prediction of depth videos under Versatile Video Coding (VVC) and observe a diverse distribution of intra prediction modes with different coding unit sizes. We propose a hybrid scheme to further boost fast depth video coding. In the first stage, we adaptively predict the HADamard (HAD) costs of intra prediction modes and initialize a candidate list according to the HAD costs. Then, the candidate list is further improved by considering the probability distribution of candidate modes with different CU sizes. Finally, early termination of CU splitting is performed at each CU depth level based on the Bayesian theorem. Our proposed method is incorporated into VVC intra prediction for fast coding of depth videos. Experiments with 7 standard sequences and 4 Quantization parameters (Qps) validate the efficiency of our method.

• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.850-858
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• 2013

In this paper, we propose a method of frame synchronization for stereoscopic 3D video to solve the viewing problem caused by synchronization errors between a left video and a right video using the temporal frame difference image depending on the movement of objects. Firstly, we compute two temporal frame difference images from the left video and the right video which are corrected the vertical parallax between two videos using rectification, and calculate two horizontal projection profiles of two temporal frame difference images. Then, we find a pair of synchronized frames of the two videos by measuring the mean of absolute difference (MAD) of two horizontal projection profiles. Experimental results show that the proposed method can be used for stereoscopic 3D video, and is robust against Gaussian noise and video compression by H.264/AVC.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.401-404
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• 2017

The 360 VR video has a format of a stereoscopic shape such as an isometric shape or a cubic shape or a cubic shape. Although these formats have different characteristics, they have in common that the resolution is higher than that of a normal 2D video. Therefore, it takes much longer time to perform coding/decoding on 360 VR video than 2D Video, so parallel processing techniques are essential when it comes to coding 360 VR video. HEVC, the state of art 2D video codec, uses Wavefront Parallel Processing (WPP) technology as a standard for parallelization. This technique is optimized for 2D videos and does not show optimal performance when used in 3D videos. Therefore, a suitable method for WPP is required for 3D video. In this paper, we propose WPP coding/decoding method which improves WPP performance on cube map format 3D video. The experiment was applied to the HEVC reference software HM 12.0. The experimental results show that there is no significant loss of PSNR compared with the existing WPP, and the coding complexity of 15% to 20% is further reduced. The proposed method is expected to be included in the future 3D VR video codecs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.721-726
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• 2011

The compression performance of HEVC (high efficiency video coding) is improved 40%, compared to H.264/AVC. Since the existing 3D video CODEC is based on H.264/AVC or MPEG-2, we can improve the compression performance when we use the proposed stereoscopic video coding method based on HEVC. Since the stereoscopic video has the temporal and inter-view correlations, the videos of the left and right cameras encode together to improve the performance. Especially, we implemented the proposed technique using HM(HEVC test model) 3.4. To compare the performance of the proposed method, we only compare the right view video which is coded using the inter-view prediction. The proposed method which is considered inter-view correlation is improved the performance which BDBR reduce about 36.24% and BDPSNR increase approximately 1.19 dB compared to the separated-coding method.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.169-174
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• 2018

There are many CCTV cameras connected to the video surveillance and monitoring center for the safety of citizens, and it is difficult for a few monitoring agents to monitor many channels of videos. In this paper, we propose an intelligent video surveillance system utilizing a safety map to efficiently monitor many channels of CCTV camera videos. The safety map establishes the frequency of crime occurrence as a database, expresses the degree of crime risk and makes it possible for agents of the video surveillance center to pay attention when a woman enters the crime risk area. The proposed gender classification method is processed in the order of pedestrian detection, tracking and classification with deep training. The pedestrian detection and tracking uses Adaboost algorithm and probabilistic data association filter, respectively. In order to classify the gender of the pedestrian, relatively simple AlexNet is applied to determine gender. Experimental results show that the proposed gender classification method is more effective than the conventional algorithm. In addition, the results of implementation of intelligent video security system combined with safety map are introduced.