• Journal of Internet Computing and Services
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• v.3 no.2
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• pp.69-77
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• 2002

Recently, Digital video is one of the important information media delivered on the Internet and playing an increasingly important role in multimedia. This paper proposes a Video Browsing Service(VBS) that provides both the video content retrieval and the video browsing by the real-time user interface on Web, For the scene segmentation and key frame extraction of video sequence, we proposes an efficient scene change detection method that combines the RGB color histogram with the $x^2$(Chi Square) histogram. Resulting key frames are linked by both physical and logical indexing, This system involves the video editing and retrieval function of a VCR's, Three elements that are the date, the field and the subject are used for video browsing. A Video Browsing Service is implemented with MySQL, PHP and JMF under Apache Web Server.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.420-432
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• 2014

In detection of moving objects from video sequences, an essential process for intelligent visual surveillance, the cast shadows accompanying moving objects are different from background so that they may be easily extracted as foreground object blobs, which causes errors in localization, segmentation, tracking and classification of objects. Most of the previous research results about moving cast shadow detection and removal usually utilize color information about objects and scenes. In this paper, we proposes a novel cast shadow removal method of moving objects in gray level video data for visual surveillance application. The proposed method utilizes observations about edge patterns in the shadow region in the current frame and the corresponding region in the background scene, and applies Laplacian edge detector to the blob regions in the current frame and the corresponding regions in the background scene. Then, the product of the outcomes of application determines moving object blob pixels from the blob pixels in the foreground mask. The minimal rectangle regions containing all blob pixles classified as moving object pixels are extracted. The proposed method is simple but turns out practically very effective for Adative Gaussian Mixture Model-based object detection of intelligent visual surveillance applications, which is verified through experiments.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.538-555
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• 2015

Event detection based on using features from a static grid can give poor results from the viewpoint of two main aspects: the position of the camera and the position of the event that is occurring in the scene. The former causes problems when training and test events are at different distances from the camera to the actual position of the event. The latter can be a source of problems when training events take place in any position in the scene, and the test events take place in a position different from the training events. Both issues degrade the accuracy of the static grid method. Therefore, this work proposes a method called a dynamic grid for event detection, which can tackle both aspects of the problem. In our experiment, we used the dynamic grid method to detect four types of event patterns: implosion, explosion, two-way, and one-way using a Multimedia Analysis and Discovery (MAD) pedestrian dataset. The experimental results show that the proposed method can detect the four types of event patterns with high accuracy. Additionally, the performance of the proposed method is better than the static grid method and the proposed method achieves higher accuracy than the previous method regarding the aforementioned aspects.

• Journal of the Society of Disaster Information
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• v.10 no.1
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• pp.33-39
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• 2014

Chemical accidents are the cause of the accident site during the initial responders to quickly and easily see materials and concentration method for the U.S. Environmental Protection Agency(EPA) is widely used in the initial response team direct reading detection equipment used. Ministry of the tubular gas detection equipment to detect direct reading detection equipment used in the event of an accident scene, and shell-and-tube gas detector for rapid detection and identification and precise analysis of causative pollutants before about strategically can identify the quantitative and qualitative useful equipment. However, those who initially respond to the scene of a direct reading detection equipment and a simple lack of understanding of how to use the numbers only because of the way you want to check the accuracy of detection results have been raising questions about the increase. The scene of the accident in order to obtain an accurate detection results used in this paper, the Ministry of Environment of gas detectors detect tubular Kitagawa and Draeger detector tube to check the reactivity of the material on-site detection of early response of those who were to raise the accuracy of the results.

• Journal of the Korea Computer Industry Society
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• v.2 no.4
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• pp.507-520
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• 2001

In this paper, a hybrid algorithm for well detecting both abrupt and gradual scene changes is proposed. This algorithm examines only the candidate intervals for speedup using the binary tree method and skips the intervals that are not candidate. For accuracy, the temporal difference of variance is used to detect the gradual scene changes while the temporal difference of histogram is used to detect the abrupt scene changes. Experimental results show that the proposed hybrid algorithm using the binary tree method works up about 10 times faster that the sequential method and is effective in detecting abrupt scene change and gradual transitions including dissolving and fading.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.9A
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• pp.2289-2304
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• 1998

For the performance analysis and traffic control of ATM networks carrying video sequences, need an appropriate video traffic model. In this paper, we propose a new traffic model for MPEG compressed videos which are widely used for any type of video applications at th emoment. The proposed modeling scheme uses scene-based traffic characteristics and considers the correlation between frames of consecutiv GOPs. Using a simple scene detection algorithm, scene changes are modeled by state transitions and the number of GOPs of a scene state is modeled by a geometric distirbution. Frames of a scene stte are modeled by mean I, P, and B frame size. For more accurate traffic modeling, quantization errors (residual bits) that the state transition model using mean values has are compensated by autoregressive processes. We show that our model very well captures the traffic chracteristics of the original videos by performance analysis in terms of autocorrelation, histogram of frame bits genrated by the model, and cell loss rate in the ATM multiplexer with limited buffers. Our model is able to perrorm translations between levels (i.e., GOP, frame, and cell levels) and to estimate very accurately the stochastic characteristics of the original videos by each level.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.868-876
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• 1999

In this paper, an efficient automatic video parsing technique on MPEG-compressed video that is fundamental for content-based indexing is described. The proposed method detects scene changes, regardless of IPB picture composition. To detect abrupt changes, the difference measure based on the dc coefficient in I picture and the macroblock reference feature in P and B pictures are utilized. For gradual scene changes, we use the macroblock reference information in P and B pictures. the process of scene change detection can be efficiently handled by extracting necessary data without full decoding of MPEG sequence. The performance of the proposed algorithm is analyzed based on precision and recall. the experimental results verified the effectiveness of the method for detecting scene changes of various MPEG sequences.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.205-212
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• 2019

Scene graph is a kind of knowledge graph that represents both objects and their relationships found in a image. This paper proposes a 3D scene graph generation model for three-dimensional indoor environments. An 3D scene graph includes not only object types, their positions and attributes, but also three-dimensional spatial relationships between them, An 3D scene graph can be viewed as a prior knowledge base describing the given environment within that the agent will be deployed later. Therefore, 3D scene graphs can be used in many useful applications, such as visual question answering (VQA) and service robots. This proposed 3D scene graph generation model consists of four sub-networks: object detection network (ObjNet), attribute prediction network (AttNet), transfer network (TransNet), relationship prediction network (RelNet). Conducting several experiments with 3D simulated indoor environments provided by AI2-THOR, we confirmed that the proposed model shows high performance.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.694-696
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• 2004

With the more sophisticated abilities development of video, object motion analysis and interpretation has become the fundamental task for the computer vision understanding. For that understanding, firstly, we seek a sum of absolute difference algorithm to apply to the motion detection, which was based on the scene. Then we will focus on the moving objects representation in the scene using spatio-temporal relations. The video can be explained comprehensively from the both aspects : moving objects relations and video events intervals.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.271-273
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• 2001

본 논문에서는 멀티미디어 데이터의 MPEG-1 비디오 데이터 정보 중 인트라 모드로 부호화된 매크로블록(macroblock) 타입 개수를 이용하여 후보 컷(cut)을 검출한다. 이렇게 검출된 후보 컷은 이전에 검출된 후보 컷과의 히스토그램 차와 화소 특징값의 분산값과 평균간을 이용하여 카메라 브레이크(camera break)와 같은 일반적인 장면전환(abrupt scene change)뿐만 아니라 커튼효과(curtaining effect)나 페이딩효과(fading effect)와 같은 점진적인 장면전환(gradual scene change)을 검출하는 방법을 제안하고 실험을 통하여 그 유용성을 보인다.