• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.129-132
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• 2003

Fixed GOP allocation in MPEG-2 cannot cope with scene change and amount of motion, which results in degradation picture quality. By finding suitable N and M and allocating dynamic GOP, the improvement of picture quality can be achieved. In this paper, N and M are determined by scene change detection and estimation of amount of motion using color histogram per each macroblock. The simulation results show that the average PSNR is improved, especially around the shot boundaries.

• 한국정보디스플레이학회:학술대회논문집
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• 2003.07a
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• pp.451-462
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• 2003

At the paper the method of 3D holographic moving image reconstruction is discused. The main idea of this method is based on the substitution of optically created static hologram by equal diffraction array created by acoustical (AO) field which formed by bulk sound waves. Such sound field can be considered as dynamic optical hologram, which is electrically controlled. At the certain moment of time when the whole hologram already formed, the reference optical beam illuminates it, and due to acoustooptical interaction the original optical image is reconstructed. As the acoustically created dynamic optical hologram is electronically controlled, it can be used for moving 3-dimentional scene reconstruction in real time. The architecture of holographic display for moving scene reconstruction is presented at this paper. The calculated variant of such display laboratory model is. given and discussed. The mathematical simulation of step by step images recording and reconstruction is given. The pictures of calculated reconstructed images are presented. The prospects, application areas, shortcomings and main problems are discussed.

• Journal of Information Display
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• v.4 no.3
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• pp.29-34
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• 2003

At the paper the method of 3D holographic moving image reconstruction is discused. The main idea of this method is based on the substitution of optically created static hologram by equal diffraction array created by acoustical (AO) field which formed by bulk sound waves. Such sound field can be considered as dynamic optical hologram, which is electrically controlled. At the certain moment of time when the whole hologram already formed, the reference optical beam illuminates it, and due to acoustooptical interaction the original optical image is reconstructed. As the acoustically created dynamic optical hologram is electronically controlled, it can be used for moving 3-dimentional scene reconstruction in real time. The architecture of holographic display for moving scene reconstruction is presented at this paper. The calculated variant of such display laboratory model is given and discussed. The mathematical simulation of step by step images recording and reconstruction is given. The pictures of calculated reconstructed images are presented. The prospects, application areas, shortcomings and main problems are discussed.

• Journal of the Korea Computer Industry Society
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• v.2 no.3
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• pp.389-396
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• 2001

In detection of a scene change of the moving pictures which has massive information capacity, the temporal sampling method has a faster searching speed and lower missing scene change detection than the sequential searching method for the whole moving pictures, yet employed searching algorithm and detection interval greatly affect missing frame and searching precision. In this study, the whole moving pictures were primarily retrieved threshold by the temporal difference of histogram scene change detection method. We suggested a dynamic threshold algorithm using cut detection interval and derived an equation formula to determine optimal primary retrieval threshold which can cut detection interval computation. Experimental results show that the proposed dynamic threshold algorithm using cut detection interval method works up about 30 percent in precision of performance than the sequential searching method.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.145-150
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• 2008

This thesis explores the problem of reconstructing a three-dimensional(3D) scene given a set of images or image sequences of the scene. It describes efficient methods for the 3D reconstruction of static and dynamic scenes from stereo images, stereo image sequences, and images captured from multiple viewpoints. Novel methods for image-based and volumetric modelling approaches to 3D reconstruction are presented, with an emphasis on the development of efficient algorithm which produce high quality and accurate reconstructions. For image-based 3D reconstruction a novel energy minimisation scheme, Iterated Dynamic Programming, is presented for the efficient computation of strong local minima of discontinuity preserving energyy functions. Coupled with a novel morphological decomposition method and subregioning schemes for the efficient computation of a narrowband matching cost volume. the minimisation framework is applied to solve problems in stereo matching, stereo-temporal reconstruction, motion estimation, 2D image registration and 3D image registration. This thesis establishes Iterated Dynamic Programming as an efficient and effective energy minimisation scheme suitable for computer vision problems which involve finding correspondences across images. For 3D reconstruction from multiple view images with arbitrary camera placement, a novel volumetric modelling technique, Embedded Voxel Colouring, is presented that efficiently embeds all reconstructions of a 3D scene into a single output in a single scan of the volumetric space under exact visibility. An adaptive thresholding framework is also introduced for the computation of the optimal set of thresholds to obtain high quality 3D reconstructions. This thesis establishes the Embedded Voxel Colouring framework as a fast, efficient and effective method for 3D reconstruction from multiple view images.

• ETRI Journal
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• v.43 no.3
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• pp.538-548
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• 2021

This paper proposes an approach to improve the performance of no-reference video quality assessment for sports videos with dynamic motion scenes using an efficient spatiotemporal model. In the proposed method, we divide the video sequences into video blocks and apply a 3D shearlet transform that can efficiently extract primary spatiotemporal features to capture dynamic natural motion scene statistics from the incoming video blocks. The concatenation of a deep residual bidirectional gated recurrent neural network and logistic regression is used to learn the spatiotemporal correlation more robustly and predict the perceptual quality score. In addition, conditional video block-wise constraints are incorporated into the objective function to improve quality estimation performance for the entire video. The experimental results show that the proposed method extracts spatiotemporal motion information more effectively and predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.

• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.43-58
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• 2013

Richmedia Service means that interactive media service can provide view with various multimedia elements(such as Video, Audio, Text) at same time. Various Multimedia elements can be serviced by Scene Description technology standards like BIFS(Binary Format for Scenes) and LASeR(Light Application Scene Representation). By providing Scene Component information, richmedia service is available to various multimedia services. so users is available to personalized services fitting temporal and spatial options. In conventional technology, when the scene is changed by user or service, mobile deletes the scene of configuration information and makes new scene of configuration information. this is a very inefficient way. In this paper, Propoesed that by using DOM(Document Object Model) method, to pass only the dynamic configuration part, changes scene method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.758-766
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• 2003

This paper proposes a tree-based hierarchical image mosaicing system using camera and object parameters for efficient video database construction. Gray level histogram difference and average intensity difference are proposed for scene change detection of input video. Camera parameter measured by utilizing least sum of square difference and affine model, and difference image is used for similarity measure of two input images. Also, dynamic objects are searched by through macro block setting and extracted by using region splitting and 4-split detection methods. Dynamic trajectory evaluation function is used for expression of dynamic objects, and blurring is performed for construction of soft and slow mosaic image.

• 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 Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.132-139
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• 2015

Visual SLAM(Simultaneous Localization And Mapping) has been used widely to estimate a mobile robot's location. Visual SLAM estimates relative motions with static visual features over image sequence. Because visual SLAM methods assume generally static features in the environment, we cannot obtain precise results in dynamic situation including many moving objects: cars and human beings. This paper presents a stereo vision based SLAM method in dynamic environment. First, we extract disparity map with stereo vision and compute optical flow. We then compute disparity change that is the estimated flow field between stereo views. After examining the disparity change value, we detect ROIs(Region Of Interest) in disparity space to determine dynamic scene objects. In indoor environment, many structural planes like walls may be determined as false dynamic elements. To solve this problem, we segment the scene into planar structure. More specifically, disparity values by the stereo vision are projected to X-Z plane and we employ Hough transform to determine planes. In final step, we remove ROIs nearby the walls and discriminate static scene elements in indoor environment. The experimental results show that the proposed method can obtain stable performance in dynamic environment.