• Journal of Advanced Navigation Technology
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• v.18 no.4
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• pp.387-392
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• 2014

Recently, various research for intelligent video surveillance system have been proposed, but the existing monitoring systems are inefficient because all of situational awareness is judged by the human. In this paper, shadow removal based moving object tracking method is proposed using the chromaticity and entropy image. The background subtraction model, effective in the context awareness environment, has been applied for moving object detection. After detecting the region of moving object, the shadow candidate region has been estimated and removed by RGB based chromaticity and minimum cross entropy images. For the validity of the proposed method, the highway video is used to experiment. Some experiments are conducted so as to verify the proposed method, and as a result, shadow removal and moving object tracking are well performed.

• Journal of Advanced Navigation Technology
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• v.10 no.4
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• pp.400-405
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• 2006

In this paper, we propose a moving object tracking algorithm by using motion estimation in UAV(Unmanned Aerial Vehicle) video. Proposed algorithm is based on generation of initial image from detected reference image, and tracking of moving object under the time-varying image. With a series of this procedure, tracking process is stable even when the UAV camera sways by correcting position of moving object, and tracking time is relatively reduced. A block matching algorithm is also utilized to determine the similarity between reference image and moving object. An experimental result shows that our proposed algorithm is better than the existing full search algorithm.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.284-288
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• 2010

Video surveillance is widely used in establishing the societal security network. In this paper, intrusion detection based on visual information acquired by static camera is proposed. Proposed approach uses background model constructed by approximated median filter(AMF) to find a foreground candidate, and detected object is calculated by analyzing motion information. Motion detection is determined by the relative size of 2D object in RGB space, finally, the threshold value for detecting object is determined by heuristic method. Experimental results showed that the performance of intrusion detection is better one when the spatio-temporal candidate informations change abruptly.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.548-566
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• 2013

The availability of technology and the abundance of experts in universities create an ample opportunity to provide a venue that allows a knowledge seeker to easily connect with and request advice from university experts. On the other hand, outsourcing provides opportunities and remains one of the emerging trends in organizations, and can very clearly observed in the Philippines. This paper describes the development of a reliable web-based approach to Knowledge Product Outsourcing (KPO) services in the Silliman Online University Learning system. The system is called an "e-Knowledge Box."It integrates Web 2.0 technologies and mechanisms, such as instant messaging, private messaging, document forwarding, video conferencing, online payments, net meetings, and social collaboration together into one system. Among the tools used are WAMP Server 2.0, PHP, BlabIM, Wordpress 3.0, Video Whisper, Red5, Adobe Dreamweaver CS4, and Virtual Box. The proposed system is integrated with the search engine in URLs, Web feeds, email links, social bookmarking, search engine sitemaps, and Web Analytics Direct Visitor Reports. The site demonstrates great web usability and has an excellent rating in functionality, language and content, online help and user guides, system and user feedback, consistency, and architectural and visual clarity. Likewise, the site was was rated as being very good for the following items: navigation navigation, user control, and error prevention and correction.

• The Journal of Korean Association of Computer Education
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• v.23 no.2
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• pp.53-64
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• 2020

As online learning forms centered on video lectures become more common and constantly increasing, the video-based learning environment applying various educational methods is also changing and developing to enhance learning effectiveness. Learner's log data has emerged for measuring the effectiveness of education in the online learning environment, and various analysis methods of log data are important for learner's customized learning prescriptions. To this end, the study analyzed learner behavior data and predictions of achievement by machine learning in video-based learning environments. As a result, interactive behaviors such as video navigation and comment writing, and learner-led learning behaviors predicted achievement in common in each model. Based on the results, the study provided implications for the design of the video learning environment.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.199-206
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• 2013

Recently, the diverse needs of the drivers for in-vehicle infotainment systems are increasing rapidly. As a result, the infotainment systems are equipped with more convenient and human-friendly high-tech features. In this paper, we designed and implemented in-vehicle multimedia infotainment system based on embedded system that was applied various multimedia to in-vehicles. The proposed system can support independent display on each screen for the multi-channel multimedia source based on one processor(1 CPU). Therefore, our system can be reduced costs compared to other systems. This system not only displays the video and audio data in storage devices but also displays CAM, T-DMB, and DVB-T multimedia contents which are supplied in real-time services. Also, our system could multi-screen displays multimedia data in smart phone using Wi-Fi. We expect that in-vehicle infotainment systems like AVN(Audio video navigation) and RSE(Rear Seat Entertainment) could be used in various applications and reduced costs.

• Journal of Advanced Navigation Technology
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• v.15 no.1
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• pp.76-82
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• 2011

Most previous work on network selection in heterogeneous wireless networks has concentrated on the quality of the network alone. Therefore, users are not satisfied with network quality based network selection due to different user preferences. To solve this problem, we proposes a QoE-aware network selection algorithm that is based on the consumption patterns of user preferences which is divided into normal user, cost-sensitive user, quality-sensitive user and video quality as well as network quality. As a result of experiments, cost-sensitive user and quality-sensitive user are satisfied with enhanced QoE by 36% and 3% from the proposed network selection algorithm compared to the normal user, respectively.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.557-561
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• 2021

A meatadata has become an essential element in order to recommend video content to users. However, it is passively generated by video content providers. In the paper, a method for automatically generating metadata was studied in the existing manual metadata input method. In addition to the method of extracting emotion tags in the previous study, a study was conducted on a method for automatically generating metadata for genre and country of production through movie audio. The genre was extracted from the audio spectrogram using the ResNet34 artificial neural network model, a transfer learning model, and the language of the speaker in the movie was detected through speech recognition. Through this, it was possible to confirm the possibility of automatically generating metadata through artificial intelligence.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.66-77
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• 2002

This paper deals with an implementation of the navigation parameter extraction technique using the TMS320C80 multimedia video processor (MVP). Especially, this Paper focuses on the relative position estimation algorithm which plays an important role in real-time operation of the overall system. Based on the relative position estimation algorithm using the images obtained at two locations, we develop a fast algorithm that can reduce large amount of computation time and fit into fixed-point processors. Then, the algorithm is reconfigured for parallel processing using the 4 parallel processors in the MVP. As a result, we shall demonstrate that the navigation parameter extraction system employing the MVP can operate at full-frame rate, satisfying real-time requirement of the overall system.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.944-954
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• 2003

People are experiencing severe problems in temporal navigation as time-based contents and platforms become more popular Relatively limited research, however, has been conducted on temporal navigation compared to that on spatial navigation. This research aims to identify efficient temporal navigation aids for time-based contents. It proposes Time Navigator, a new temporal navigation system based on the episodic indexing theory, and evaluates its efficiency through two experiments with a computer-based simulator for digital TV The video contents of digital TV was focused on because it is one of the most representative time-based contents and platforms. Our results indicate that Time Navigator helps people navigate time -based contents more effectively. Its effects increase as the contents include more narratives.