• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.563-565
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• 2021

The most important feature of the recently increasing content providing service is that the amount of content increase over time is very large. Accordingly, the importance of user curation is increasing, and various techniques are used to implement it. In this paper, among the techniques for video recommendation, the analysis technique using voice data and subtitles and the video comparison technique based on keyframe extraction are compared with the results of implementing and applying the video content of real big data. In addition, through the comparison result, a video content environment to which each analysis technique can be applied is proposed.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.153-160
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• 2021

With the advent of the "age of video" due to the simplification of video content production and the convenience of broadcasting channel operation, review videos on various products are drawing attention. We proposes RASIA, an integrated reliability analysis system based on verbal and nonverbal sentiment analysis of review videos. RASIA extracts and quantifies each emotional value obtained through language sentiment analysis and facial analysis of the reviewer in the video. Subsequently, we conduct an integrated reliability analysis of standardized verbal and nonverbal sentimental values. RASIA provide an new objective indicator to evaluate the reliability of the review video.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.591-596
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• 1999

In this paper, we present a joint quality control system to be able to accurately control the relative picture quality among the video programs in terms of PSNR. The joint quality control system allows variable bit rate (VBR) for each video program to maintain the pre-determined relative picture quality among the aggregated video programs while keeping a constant sum of the bit rates for all programs to be transmitted over a single constant bit rate (CBR) channel. This is achieved by simultaneous controlling the video encoders to generate VBR video streams at the central controller. Furthermore we also suggest buffer regulation method based on the analysis of the constraints imposed by sender/receiver buffer sizes and total transmission rate. Through various simulation results, it is found that our quality control systems guarantee that the video buffers do not overflow and underflow and the quality control errors do not exceed 0.1 ㏈.

• Journal of Multimedia Information System
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• v.4 no.2
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• pp.73-78
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• 2017

The Future Video Coding (FVC) is a new state of the art video compression standard that is going to standardize, as the next generation of High Efficiency Video Coding (HEVC) standard. The FVC standard applies newly designed block structure, which is called quadtree plus binary tree (QTBT) to improve the coding efficiency. Also, intra and inter prediction parts were changed to improve the coding performance when comparing to the previous coding standard such as HEVC and H.264/AVC. Experimental results shows that we are able to achieve the average BD-rate reduction of 25.46%, 38.00% and 35.78% for Y, U and V, respectively. In terms of complexity, the FVC takes about 14 times longer than the consumed time of HEVC encoder.

• Proceedings of the KAIS Fall Conference
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• 2011.05a
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• pp.371-374
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• 2011

Recently, retrieval of various video data has become an important issue as more and more multimedia content services are being provided. To effectively deal with video data, a semantic-based retrieval scheme that allows for processing diverse user queries and saving them on the database is required. In this regard, this paper proposes a semantic-based video retrieval system that allows the user to search diverse meanings of video data for electrical safety-related educational purposes by means of automatic annotation processing. If the user inputs a keyword to search video data for electrical safety-related educational purposes, the mobile agent of the proposed system extracts the features of the video data that are afterwards learned in a continuous manner, and detailed information on electrical safety education is saved on the database. The proposed system is designed to enhance video data retrieval efficiency for electrical safety-related educational purposes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3668-3684
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• 2021

Video action recognition is widely used in video surveillance, behavior detection, human-computer interaction, medically assisted diagnosis and motion analysis. However, video action recognition can be disturbed by many factors, such as background, illumination and so on. Two-stream convolutional neural network uses the video spatial and temporal models to train separately, and performs fusion at the output end. The multi segment Two-Stream convolutional neural network model trains temporal and spatial information from the video to extract their feature and fuse them, then determine the category of video action. Google Xception model and the transfer learning is adopted in this paper, and the Xception model which trained on ImageNet is used as the initial weight. It greatly overcomes the problem of model underfitting caused by insufficient video behavior dataset, and it can effectively reduce the influence of various factors in the video. This way also greatly improves the accuracy and reduces the training time. What's more, to make up for the shortage of dataset, the kinetics400 dataset was used for pre-training, which greatly improved the accuracy of the model. In this applied research, through continuous efforts, the expected goal is basically achieved, and according to the study and research, the design of the original dual-flow model is improved.

• International Journal of Contents
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• v.18 no.1
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• pp.27-39
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• 2022

Short videos are becoming more popular in mobile Internet age. Not only people's media consumption patterns have been changed by the rise of this new media form, but also it has posed challenges to public psychological well-being. For many netizens, their entertainment needs have been met by watching short videos. However, many side effects, such as addiction and anxiety, reduce users' subjective well-being instead of satisfying the entertainment motivation after watching short videos. Therefore, it has become a significant research problem in short videos to figure out how to get audiences to watch short videos on a regular basis while avoiding side effects like anxiety and addiction and improving audiences' subjective well-being. Based on the theory of Internet addiction, this study analyzed short video users using the 2×2×2 research method and explored the relationship between the length of use, addiction, anxiety, and subjective well-being of short video users. The results showed that short video users with different usage lengths showed significant differences in addiction, anxiety, subjective well-being, and online social support; innovative different short video users showed significant differences in addiction and anxiety, as well as a triadic relational interaction of short video users' anxiety under the interaction with self-efficacy and online social support. This study contributes to the advancement of internet addiction theory research and application, assisting short video users in avoiding addiction and anxiety, and improving the subjective well-being of short video users, thereby promoting the growth of the short video industry.

• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.1047-1057
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• 2015

In this paper, we propose an effective wireless transmission technology, under poor wireless transmission channel surroundings caused by speedy flying, that are able to transmit high quality video recording information and surveillance data via accessing to various wireless networking services architecture such as One-on-One, Many-on-One, One-on-Many, Over the Horizon. The Real-Time Position Analysis(RAPA) method is also suggested to provide more meaningful video information of shooting area. The suggested wireless transmission technology and RAPA can make remote control of UAV's flight route to get valuable topography information. Because of the benefit to get both of video information and GPS data of shooting area simultaneously, the result of study can be applied to various application sphere including UAV that requires high speed wireless transmission.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.35-45
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• 2016

The purpose of this study is to examine factors that influence mobile video services' satisfaction. 362 users who use both DMB and mobile video services complete the questionnaires measuring 6 attribute level satisfactions and total satisfaction of mobile video services, TV contents broadcasting status in mobile video services. The data are analyzed by using frequency analysis, Chi-square test, t-test/F-test, multiple regression and moderated multiple regression. The results of the study are as follows: First, diverse contents, image quality, video streaming quality, user convenience, and data consumption volume affect total satisfaction of mobile video services. Second, TV contents broadcasting status in mobile video services doesn't show positive moderation effect on the relationship between attribute level satisfaction and total satisfaction. Based on the results, the implications and limitations of this study are discussed.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.215-220
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• 2022

Emotion recognition is one of the most important and challenging areas of computer vision. Nowadays, many studies on emotion recognition were conducted and the performance of models is also improving. but, more research is needed on emotion recognition and sentiment analysis of video viewers. In this paper, we propose an emotion analysis system the includes a sentiment analysis model and an interest prediction model. We analyzed the emotional patterns of people watching popular and unpopular videos and predicted the level of interest using the emotion analysis system. Experimental results showed that certain emotions were strongly related to the popularity of videos and the interest prediction model had high accuracy in predicting the level of interest.