• Journal of Multimedia Information System
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• v.8 no.3
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• pp.147-158
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• 2021

Versatile Video Coding (VVC) is the latest video coding standard developed by Joint Video Exploration Team (JVET). In VVC, the quadtree plus multi-type tree (QT+MTT) structure of coding unit (CU) partition is adopted, and its computational complexity is considerably high due to the brute-force search for recursive rate-distortion (RD) optimization. In this paper, we aim to reduce the time complexity of inter-picture prediction mode since the inter prediction accounts for a large portion of the total encoding time. The problem can be defined as classifying the split mode of each CU. To classify the split mode effectively, a novel convolutional neural network (CNN) called multi-level tree (MLT-CNN) architecture is introduced. For boosting classification performance, we utilize additional information including inter-picture information while training the CNN. The overall algorithm including the MLT-CNN inference process is implemented on VVC Test Model (VTM) 11.0. The CUs of size 128×128 can be the inputs of the CNN. The sequences are encoded at the random access (RA) configuration with five QP values {22, 27, 32, 37, 42}. The experimental results show that the proposed algorithm can reduce the computational complexity by 11.53% on average, and 26.14% for the maximum with an average 1.01% of the increase in Bjøntegaard delta bit rate (BDBR). Especially, the proposed method shows higher performance on the sequences of the A and B classes, reducing 9.81%~26.14% of encoding time with 0.95%~3.28% of the BDBR increase.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.230-240
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• 2022

Sharing of online videos via internet is an emerging and important concept in different types of applications like surveillance and video mobile search in different web related applications. So there is need to manage personalized web video retrieval system necessary to explore relevant videos and it helps to peoples who are searching for efficient video relates to specific big data content. To evaluate this process, attributes/features with reduction of dimensionality are computed from videos to explore discriminative aspects of scene in video based on shape, histogram, and texture, annotation of object, co-ordination, color and contour data. Dimensionality reduction is mainly depends on extraction of feature and selection of feature in multi labeled data retrieval from multimedia related data. Many of the researchers are implemented different techniques/approaches to reduce dimensionality based on visual features of video data. But all the techniques have disadvantages and advantages in reduction of dimensionality with advanced features in video retrieval. In this research, we present a Novel Intent based Dimension Reduction Semi-Supervised Learning Approach (NIDRSLA) that examine the reduction of dimensionality with explore exact and fast video retrieval based on different visual features. For dimensionality reduction, NIDRSLA learns the matrix of projection by increasing the dependence between enlarged data and projected space features. Proposed approach also addressed the aforementioned issue (i.e. Segmentation of video with frame selection using low level features and high level features) with efficient object annotation for video representation. Experiments performed on synthetic data set, it demonstrate the efficiency of proposed approach with traditional state-of-the-art video retrieval methodologies.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.258-261
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• 2014

The era of realistic broadcast with high fidelity has come after the wide-spread distribution of UHD display and the transmission of UHD experimental broadcast in CATV. However, UHD broadcast now has constraint because it requires much amount of bandwidth and data in broadcasting transmission and production system. Not only HEVC(High Efficiency Video Codec) which has more than two times higher compression rate but also cloud-based editing system would be the key to solve the problems above. Also, fast scene change detection of videos is needed to index and search UHD videos smoothly. In this paper, therefore, a method is proposed to index and search the scene change information of large volume UHD videos compressed with high-efficiency codec. Application usages of fast detection of scene change information in various UHD video environments are considered by using this algorithm.

• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.741-750
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• 2003

$MTP^{TM}$ guarantees high bandwidth that is necessary to tansmit high qualify full motion video data effectively. In other hand TCP/IP which is used for information search does not guarentee high bandwidth as that in $MTP^{TM}$. Therefore VOD service system that searches information manged by DBMS and transmits required full motion video data should control different kinds of protocol simultaneously. This paper describes the configuration of VODB system that has solved these problems.

• Journal of Korea Game Society
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• v.11 no.5
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• pp.67-78
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• 2011

This paper introduces an efficient and satisfactory search interface that enables users to browse and find the video data they want from a massively huge video database widely used in various multimedia environment. The target user group is information analysts at US defense industry or governmental intelligence agencies whose job is to identify a certain person from a lot of video footage taken from CCTV(Closed-circuit Television) cameras. For the first user test, we suggested the CAVE-like virtual reality interface to be the most optimal for the tasks we designed for, so we compared this interface with desktop interface. The softwares and database developed and optimized for each task were used in this user test. For the second user test, we researched on what input devices would be most optimal for enhancing efficiency of search task in the CAVE-like virtual reality system. Especially we focused our effort on measuring the effectiveness and user satisfaction of three different types of devices that embody gestural interface input system that encourages users' ergonomic control of the interface. We also measured the time consumed for performing each task to find out the most efficient input device among the ones tested.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.286-295
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• 2012

To meet the increased demand of video-on-demand (VoD) services, peer-to-peer (P2P) mesh-based multiple video approaches have been recently proposed, where each peer is able to find a video segment interested without resort to the video server. However, they have not considered the constraint of the server's upload bandwidth and the fairness between upload and download amounts at each peer. In this paper, we propose a novel P2P VoD streaming system, named peer cache adaptation (PECAN) where each peer adjusts its cache capacity adaptively to meet the server's upload bandwidth constraint and achieve the fairness. For doing so, we first propose a new cache replacement algorithm that designs the number of caches for a segment to be proportional to its popularity. Second, we mathematically prove that if the cache capacity of a peer is proportional to its segment request rate, the fairness between upload and download amounts at each peer can be achieved. Third, we propose a method that determines each peer's cache capacity adaptively according to the constraint of the server's upload bandwidth. Against the proposed design objective, some selfish peers may not follow our protocol to increase their payoff. To detect such peers, we design a simple distributed reputation and monitoring system. Through simulations, we show that PECAN meets the server upload bandwidth constraint, and achieves the fairness well at each peer. We finally verify that the control overhead in PECAN caused by the search, reputation, and monitoring systems is very small, which is an important factor for real deployment.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.313-318
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• 2017

In general, users of design software such as Photoshop, search for information online when they want to obtain related knowledge. However, it is very difficult to find the exact information they want about designs because available knowledge sharing systems are very broad in what they manage, and it is rare that such systems would provide any design-specific Q&A or exchange of information functionality. In the paper we development a video based system for sharing design knowledge that supplies Q&A, lecture, knowledge trade function etc. utilizing multimedia like text, image and video reflecting the characteristics of design knowledge. The system are expected to contribute to the competitiveness of products through sharing design knowledge. In the near future the system will need to expand to a framework that can be shared with a variety of knowledge, as well as design knowledge.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.55-61
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• 2016

For the purpose of video security equipment is to protect personal property and life against from terrorism or recent threats. In this study, if you proceed with the recorded data search, we propose a method for increasing the user's search convenience. It has predefined data structure which is between camera's movement path and relationship. Also, design and implement a tool that automatically generates a files which has inter camera related information on the control center in a multi-camera is installed environment. Using generated file, minimize searching time and increase searching efficiency.

• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.238-244
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• 2020

The development and distribution rate of smartphones have progressed so rapidly that it is safe for the entire nation to use them in the smart age, and the use of smartphones has become an essential medium for the use of domestic media content, and many people are using various contents regardless of gender, age, or region. Recently, various media outlets have been consuming video content for online learning, indicating that learners utilize video content online for learning. In the previous research, satisfaction studies were conducted according to the type of content, and the improvement plan was necessary because no research was conducted on how to evaluate the learning content itself and provide it to learners. In this paper, we would like to propose a system through evaluation and review of learning content itself as a way to improve the way of providing video content for learning and quality learning content.

• Journal of Korean Library and Information Science Society
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• v.31 no.1
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• pp.229-258
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• 2000

The growth of digital image an video archives is increasing the need for tools that efficiently search through large amount of visual dta. Retrieval of visual data is important issue in multimedia database. We are using contented-based visual data retrieval method for efficient retrieval of visual data. In this paper, we introduced fundamental techniques using characteristic values of image data and indexing techniques required for content-based visual retrieval. In addition we introduced content-based visual retrieval system for use of digital library.