• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.306-309
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• 2008

A system realization for video surveillance with interframe probability distribution analysis is presented in this paper. The system design is based on a high performance DSP processor, video surveillance is implemented by analyzing interframe probability distribution for scanning objects in a restricted area and the video analysis algorithm is decided for forming a different image from the probability distribution of several frames compressed by the standardized JPEG. The algorithm processing time of D1($720{\times}480$) image per frame is 85ms.

• Journal of Distribution Science
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• v.21 no.9
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• pp.43-53
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• 2023

Purpose: This study aims to examine the demographic similarities and differences in objectives, methodology, and findings of previous studies in the context of gaining financial literacy using videos. This study employs a systematic review design. Research design, data and methodology: Based on the content analysis method, 15 articles were chosen from Scopus and Science Direct during 2015-2020. After formulating the research questions, the paper identification process, screening, eligibility, and quality appraisal are discussed in the methodology. The keywords for the advanced search included "Financial literacy," "Financial Education," and "Video". Results: The results of this study indicate the effectiveness of learning financial literacy using videos. Significant results were obtained when students interacted with the video content distribution. The findings of this study provide an overview and lead to a better understanding of the use of video in financial literacy. Conclusions: This study is important as a guide for educators in future research and practice planning. A systematic review on this topic is the research gap. Video learning was active learning that involved student-centered activities that help students engage with financial literacy. By conducting a systematic review, researchers and readers may also understand how extending an individual's financial literacy may change after financial education.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1064-1069
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• 2008

A system design and realization for video surveillance with interframe probability distribution analyzation is presented in this paper. The system design is based on a high performance DSP professor, video surveillance is implemented by analyzing interframe probability distribution using trivariate normal distribution(weight, mean, variance) for scanning objects in a restricted area and the video analysis algorithm is decided for forming a different image from the probability distribution of several frame compressed by the standardized JPEG. The system processing time of D1$(720{\times}480)$ image per frame is 85ms and enables to process the system at 12 frames per second. An object surveillance about the restricted area by rules is extracted to 100% unless object is moved faster.

• ETRI Journal
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• v.33 no.3
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• pp.454-457
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• 2011

In this letter, we propose a new quality measurement method to identify the causes of video quality degradation for IP-based video services. This degradation mainly results from network performance issues and video compression. The proposed algorithm identifies the causes based on statistical feature values from blocky block distribution in degraded IP-based videos. We found that the sensitivity and specificity of the proposed algorithm are 93.63% and 91.99%, respectively, in comparison with real error types and subjective test data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.107-115
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• 2011

In this paper, we proposed fast and efficient algorithm for detecting near-duplication based on content based retrieval in large scale video database. For handling large amounts of video easily, we split the video into small segment using scene change detection. In case of video services and copyright related business models, it is need to technology that detect near-duplicates, that longer matched video than to search video containing short part or a frame of original. To detect near-duplicate video, we proposed motion distribution and frame descriptor in a video segment. The motion distribution descriptor is constructed by obtaining motion vector from macro blocks during the video decoding process. When matching between descriptors, we use the motion distribution descriptor as filtering to improving matching speed. However, motion distribution has low discriminability. To improve discrimination, we decide to identification using frame descriptor extracted from selected representative frames within a scene segmentation. The proposed algorithm shows high success rate and low false alarm rate. In addition, the matching speed of this descriptor is very fast, we confirm this algorithm can be useful to practical application.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.113-121
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• 2012

In this paper, we proposed fast and efficient algorithm for detecting near-duplication based on content based retrieval in large scale video database. For handling large amounts of video easily, we split the video into small segment using scene change detection. In case of video services and copyright related business models, it is need to technology that detect near-duplicates, that longer matched video than to search video containing short part or a frame of original. To detect near-duplicate video, we proposed motion distribution and frame descriptor in a video segment. The motion distribution descriptor is constructed by obtaining motion vector from macro blocks during the video decoding process. When matching between descriptors, we use the motion distribution descriptor as filtering to improving matching speed. However, motion distribution has low discriminability. To improve discrimination, we decide to identification using frame descriptor extracted from selected representative frames within a scene segmentation. The proposed algorithm shows high success rate and low false alarm rate. In addition, the matching speed of this descriptor is very fast, we confirm this algorithm can be useful to practical application.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2197-2207
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• 1997

In this paper, we propose a video data segmentation method using edge and color distribution of video frames and also develop a video browser by using the proposed algorithm. To segment a video, we use a 644-bin HSV color histogram and the edge information which generated with automatic threshold method. We consider scene's characteristics by using positions and colo distributions of object in each frame. We develop a hierarchical and a shot-based browser for video browsing. We also show that our proposed method is less sensitive to light effects and more robust to motion effects than previous ones like a histogram-based method by testing with various video data.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.10-14
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• 2015

Video Content owners seek to squeeze the maximum amount of revenue from their assets via distribution into more territories. Digital Cinema Package(DCP), trusted solution to distribute protected content to theaters, caters to relatively small user base, which limits revenue. With the growth of the Internet & other digital media, the economics of media content has changed dramatically. Security remains main concern to deliver content to millions of consumers using intelligent digital display devices like Tablets, Smartphones, Smart TVs, Desktop & Laptop. By making the video content available to this segment securely, content owners will benefit from increased revenue. Through this paper we propose Open Source HomeDCP model to distribute the content to home users for offline viewing. We propose to include other open source CODEC than JPEG2000/MPEG2, which are specifically designed for theatrical performance. Final image size will be further reduced considering the display device resolution where video will be finally played. Key Delivery Message(KDM) system to be altered to suit new devices. This will be a big boost to Content Economy as content owners would be able to distribute the content securely to the wider audience & ensure more revenue.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.404-407
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• 2009

Bluetooth Video Distribution Profile (VDP) defines the protocol and procedures that realize the distribution of video content compressed in a specific format for the efficient use of the limited bandwidth. In this paper, we describe the design of VDP tester based on TTCN-2 (Tree and Tabular Combined Notation), a language standardized by ISO for the specification of tests for real-time and communicating systems. Our work was carried out as a part of supporting a new profile testing module for VDP in PTS (Profile Tuning Suite), a reference test system for Bluetooth interoperability testing. Test demonstration for the interoperability with various VDP solutions at the PTS session in UPF30 (Unplug Fest) showed the validity of the developed tester. Eventually, we introduce the PTS architecture, and show the design and implementation of VDP tester included in the released PTS 3.0 in this paper.

• Journal of Distribution Science
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• v.20 no.11
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• pp.121-129
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• 2022

Purpose: Artificial intelligence is widely used, particularly in the popular neural network theory called Deep learning. The improvement of computing speed and capability expedited the progress of Deep learning applications. The application of Deep learning in education has various effects and possibilities in creating and managing educational content and services that can replace human cognitive activity. Among Deep learning, Deep fake technology is used to combine and synchronize human faces with voices. This paper will show how to develop e-Learning content videos using those technologies and open-source tools. Research design, data, and methodology: This paper proposes 4 step development process, which is presented step by step on the Google Collab environment with source codes. This technology can produce various video styles. The advantage of this technology is that the characters of the video can be extended to any historical figures, celebrities, or even movie heroes producing immersive videos. Results: Prototypes for each case are also designed, developed, presented, and shared on YouTube for each specific case development. Conclusions: The method and process of creating e-learning video contents from the image, video, and audio files using Deep fake open-source technology was successfully implemented.