• Journal of Digital Convergence
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• v.15 no.10
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• pp.445-454
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• 2017

Recently, playing musical instruments in the application or website which is a sort of playing has been catching on for ordinary people even though they don't know how to play musical instruments. It appears that such playing has randomness which is quite natural. Thus, 'Random operation method' which induces the observing audience and changes them to manage actively is developed and suggested for the image system in this paper by utilizing Launch Pad, based on theoretical background and case analysis. Step Sequencer was developed in two ways: the image system is realized with Step Sequencer by connecting external program or made as clips to arrange them for each key on Launch Pad and implement, which is keyboard launch type.

• The Research Journal of the Costume Culture
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• v.18 no.1
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• pp.161-176
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• 2010

This study attempts to develop e-learning contents for the "fashion information analysis," which should be performed in combination of theory and practice in fashion education, in a recent Web-based education environment. The e-learning contents are developed by using the three steps of analysis, design and development. In order to analyze the requirements of curricula, the status and content of fashion information related curricular provided by general universities and cyber universities are analyzed, and then on the basis of this analysis the education objectives and detailed contents of e-learning contents are determined. Design and development of e-learning contents consist of the types, education menus and education form. The types of e-learning contents are developed into an education form combined with tutorial and practice/activity types. The education menus are comprised of syllabic, the profiles of professors and students, announcements, questions and answers regarding respect subjects, materials, and notes. Meanwhile, the education form consists of the following sections: "Before the Learning", "Learning", "Review Questions", "Final Review", "References", and "Practice", "Before the Learning" consists of two parts of a theory lecture that is composed of video clips and Power-Point presentations, and practice that consists of an audio(or video) lecture and illustration or Photoshop software execution window.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.191-197
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• 2022

This study proposes an image-based Pose Intention Network (PIN) algorithm for rehabilitation via patients' intentions. The purpose of the PIN algorithm is for enabling an active rehabilitation exercise, which is implemented by estimating the patient's motion and classifying the intention. Existing rehabilitation involves the inconvenience of attaching a sensor directly to the patient's skin. In addition, the rehabilitation device moves the patient, which is a passive rehabilitation method. Our algorithm consists of two steps. First, we estimate the user's joint position through the OpenPose algorithm, which is efficient in estimating 2D human pose in an image. Second, an intention classifier is constructed for classifying the motions into three categories, and a sequence of images including joint information is used as input. The intention network also learns correlations between joints and changes in joints over a short period of time, which can be easily used to determine the intention of the motion. To implement the proposed algorithm and conduct real-world experiments, we collected our own dataset, which is composed of videos of three classes. The network is trained using short segment clips of the video. Experimental results demonstrate that the proposed algorithm is effective for classifying intentions based on a short video clip.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.612-628
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• 2020

This paper presents a new approach for detecting abnormal behaviors in complex surveillance scenes where anomalies are subtle and difficult to distinguish due to the intricate correlations among multiple objects' behaviors. Specifically, a cascaded probabilistic topic model was put forward for learning the spatial context of local behavior and the temporal context of global behavior in two different stages. In the first stage of topic modeling, unlike the existing approaches using either optical flows or complete trajectories, spatio-temporal correlations between the trajectory fragments in video clips were modeled by the latent Dirichlet allocation (LDA) topic model based on Markov random fields to obtain the spatial context of local behavior in each video clip. The local behavior topic categories were then obtained by exploiting the spectral clustering algorithm. Based on the construction of a dictionary through the process of local behavior topic clustering, the second phase of the LDA topic model learns the correlations of global behaviors and temporal context. In particular, an abnormal behavior recognition method was developed based on the learned spatio-temporal context of behaviors. The specific identification method adopts a top-down strategy and consists of two stages: anomaly recognition of video clip and anomalous behavior recognition within each video clip. Evaluation was performed using the validity of spatio-temporal context learning for local behavior topics and abnormal behavior recognition. Furthermore, the performance of the proposed approach in abnormal behavior recognition improved effectively and significantly in complex surveillance scenes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.21-28
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• 2008

This paper proposes a novel reduced-reference assessment method for video quality assessment, in which one-dimensional (1-D) histograms of motion vectors (MVs) are used as features of videos. The proposed method is more efficient than the conventional methods in view of computation time, because the proposed quality metric decodes MVs directly from video stream in the parsing process instead of reconstructing the distorted video at the receiver. Moreover, in view of data size, the propose method is efficient because a sender transmits 1-D histograms of MVs accumulated over whole input video sequences. Here, we use 1-D histograms of MVs accumulated over the whole video sequences, which is different from the conventional methods that assessed each image independently. For testing the similarity between histograms, we use histogram intersection and histogram difference methods. We compare the proposed method with the conventional methods for 52 video clips, which are coded under varying bit rate, image size, and frame rate. Experimental results show that the proposed method is more efficient than the conventional methods and that the proposed method is more similar to the mean opinion score (MOS) than conventional algorithms.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.1
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• pp.1-12
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• 2003

Recently, many researches into distributed processing on Internet, and multimedia data processing have been performed. Rapid and convenient multimedia services supplied with high quality and high speed are to be needed. In this paper, we design and implement clip-based video retrieval system on the Web enviroment in real-time. Our system consists of the content-based indexing system supporting convenient services for video content providers, and the Web-based retrieval system in order to make it easy and various information retrieval for users in the Web. Three important methods are used in the content-based indexing system, key frame extracting method by dividing video data, clip file creation method by clustering related information, and video database construction method by using clip unit. In Web-based retrieval system, retrieval method ny using a key word, two dimension browsing method of key frame, and real-time display method of the clip are used. In this paper, we design and implement the system that supports real-time display method of the clip are used. In this paper, we design and implement the system that supports real-time retrieval for video clips on Web environment and provides the multimedia service in stability. The proposed methods show a usefulness of video content providing, and provide an easy method for serching intented video content.

• Journal of KIISE:Databases
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• v.37 no.3
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• pp.127-136
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• 2010

With rapid growth of information and computer communication technologies, the numbers of digital documents including multimedia data have been recently exploded. In particular, news video database and news video mining have became the subject of extensive research, to develop effective and efficient tools for manipulation and analysis of news videos, because of their information richness. However, many research focus on browsing, retrieval and summarization of news videos. Up to date, it is a relatively early state to discover and to analyse the plentiful latent semantic knowledge from news videos. In this paper, we propose the news video mining system based on multi-modal approach and text mining, which uses the visual-textual information of news video clips and their scripts. The proposed system systematically constructs a taxonomy of news video stories in automatic manner with hierarchical clustering algorithm which is one of text mining methods. Then, it multilaterally analyzes the topics of news video stories by means of time-cluster trend graph, weighted cluster growth index, and network analysis. To clarify the validity of our approach, we analyzed the news videos on "The Second Summit of South and North Korea in 2007".

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.109-110
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• 2017

파노라마 영상은 $360^{\circ}$ 방향의 모든 경치를 담는 기법을 말한다. 파노라마 영상은 전문적 기술자들이 여러 영상을 정합하여 제작되었지만, 기술이 점차 발전하여 현재는 일반 사용자들도 스마트 폰을 이용하여 손쉽게 파노라마 영상을 제작할 수 있다. 하지만 이는 파노라마 정지영상에 한해있으며 아직까지 파노라마 동영상은 제작에 있어서 기술적 어려움이 있다. 최근 들어서 파노라마 동영상 제작을 위한 여러 동영상 간의 시간축 동기화는 연구되었는데 연속되는 프레임들을 하나의 시퀀스로 묶어 시퀀스 단위로 키포인트 및 디스크립터를 추출 및 비교를 통해 동영상 간의 시간축을 동기화시키는 방향으로 나갔다. 하지만 동영상 시퀀스 간의 간격이 좁아 중복되는 데이터의 양이 많아 디스크립터 비교 연산 시간이 오래 걸리고, 동영상 간의 시퀀스 단위만으로 비교하기 인해 프레임 단위의 정확한 시간축 동기화에 어려움이 있었다. 본 논문에서는 이전 연구의 단점을 개선하여 여러 동영상 간의 시간축을 하나로 동기화시키는 기술을 최적화하는 방법을 제안한다.

• Journal of Technology Innovation
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• v.15 no.2
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• pp.103-122
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• 2007

This paper examines the social development process of technological innovation for national emergency management. There are relatively few studies on how technological innovations are developed and deployed within social context. This paper investigates innovation processes within social contexts and the role of innovation actors such as citizens, government, and private sector. The the Real-time Disaster Management System (RDMS) is an innovation for citizens to transmit digital images and video clips on disaster toward professional organizations to respond to disasters. This case shows how an innovation in disaster management was developed by social interactions, how open innovation mechanism was deployed, and how end-users involved in innovation processes for disaster management. Finally this paper suggests implications to accelerate innovations for social welfare and social change.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.11a
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• pp.82-83
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• 2017

파노라마 영상은 최근 몇 년 사이 스마트 폰을 사용하는 일반 사용자에게 손쉽게 제작할 수 있게 되었다. 하지만 파노라마 동영상은 기술상의 어려움이 있다. 파노라마 동영상을 제작하기 위해서는 두 대 이상의 스마트 폰으로 동시에 촬영을 하여야 하는데, 하드웨어의 차이로 인해 시간축을 동기화하는데 어려움이 발생한다. 이러한 어려움을 극복하기 위해 영상 정보를 이용한 시간축 동기화도 시도되었다. 하지만 영상 정보를 이용한 시간축 동기화에도 어려움이 있다. 영상 정보를 이용하기 때문에 계산복잡도가 높고 영상 내 움직임으로 인해 시간축 동기화 정확도도 떨어진다. 본 논문에서는 영상 정보를 이용하는 대신 소리 파형을 이용한 시간축동기화 기법을 제안한다. 소리 파형 이미지를 이용하여 시간축을 동기화하기 때문에 정확도가 향상되고 시간축 동기화 프로세싱 시간이 단축되는 것을 확인할 수 있다.