• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.49-56
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• 2009

Recently, a generation of high quality mosaic images from video sequences has been attempted by a variety of investigations. Among the matter of investigation, in this paper, generation on stereo mosaic utilizing airborne-video sequence images is focused upon. The stereo mosaic is made by creating left and right mosaic which are fabricated by front and rear slices having different viewing angle in consecutive video frames. For making the stereo mosaic, motion parameters which are able to define geometric relationship between consecutive video frames are determined. For determining motion parameters, affine model which is able to explain relative motion parameters is applied by this paper. The mosaicing method using relative motion parameters is called by free mosaic. The free mosaic proposed in this paper consists of 4 step processes: image registration with reference to first frame using affine model, front and rear slicing, stitching line definition and image mosaicing. As the result of experiment, the left and right mosaic image, anaglyphic image for stereo mosaic images are showed and analyzed y-parallax for checking accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1C
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• pp.53-61
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• 2008

In this paper, we propose an algorithm for generation of multi-view video from conventional 2 dimensional video. Color and motion information of an object are used for segmentation and from the segmented objects, multi-view video is generated. Especially, color information is used to extract the boundary of an object that is barely extracted by using motion information. To classify the homogeneous regions with color, luminance and chrominance components are used. A pixel-based motion estimation with a measurement window is also performed to obtain motion information. Then, we combine the results from motion estimation and color segmentation and consequently we obtain a depth information by assigning motion intensity value to each segmented region. Finally, we generate multi-view video by applying rotation transformation method to 2 dimensional input images and the obtained depth information in each object. The experimental results show that the proposed algorithm outperforms comparing with conventional conversion methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.859-869
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• 2012

In this paper, a new method to efficiently generate the 3-D(three-dimensional) video holograms for 3-D moving scenes, which is called here the TSR-N-LUT method, is proposed by the combined use of temporal-spatial redundancy(TSR) of 3-D video images and novel look-up table(N-LUT) technique. That is, in the proposed scheme, with the differential pulse code modulation (DPCM) algorithm, temporally redundancy redundant data in the inter-frame of a 3-D video images are removed between the frames, and then inter-line redundant data in the inter-frame of 3-D video images are also removed by using the DPCM method between the lines. Experimental results show that the proposed method could reduced the number of calculated object points and the calculation time of one object point by 23.72% and 19.55%, respectively on the average compared to the conventional method. Good experimental results with 3-D test moving pictures finally confirmed the feasibility of the proposed method to the fast generation of CGH patterns of the 3-D video images.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.23-29
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• 2019

In this paper, the mood of images was classified into eight categories through a deep convolutional neural network and video was automatically generated using proper background music. Based on the collected image data, the classification model is learned using a multilayer perceptron (MLP). Using the MLP, a video is generated by using multi-class classification to predict image mood to be used for video generation, and by matching pre-classified music. As a result of 10-fold cross-validation and result of experiments on actual images, each 72.4% of accuracy and 64% of confusion matrix accuracy was achieved. In the case of misclassification, by classifying video into a similar mood, it was confirmed that the music from the video had no great mismatch with images.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.826-836
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• 2016

Increase of hypertext transfer protocol (HTTP)-based video popularity causes that broadband and Internet service providers' links transmit mainly multimedia content. Network planning, traffic engineering or congestion control requires understanding of the statistical properties of network traffic; therefore, it is desirable to investigate the characteristic of traffic traces generated, among others, by systems which employ adaptive bit-rate streaming. In our work, we investigate traffic originating from 120 client-server pairs, situated in an emulated laboratory environment, and multiplexed onto a single network link. We show that the structure of the traffic is distinct from the structure generated by first and second generation of HTTP video systems, and furthermore, not similar to the structure of general Internet traffic. The obtained traffic exhibits negative correlations, anti-persistence, and its distribution function is skewed to the right. Furthermore, we show that the traffic generated by clients employing the same or similar play-out strategies is positively correlated and synchronised (clustered), whereas traffic originated from different play-out strategies shows negative or no correlations.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.110-114
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• 2015

This paper reports a novel object-detection technique in video sequences. The proposed algorithm consists of detection of objects in illuminated and occluded videos by using object features and a neural network technique. It consists of two functional modules: region-based object feature extraction and continuous detection of objects in video sequences with region features. This scheme is proposed as an enhancement of the Lowe's scale-invariant feature transform (SIFT) object detection method. This technique solved the high computation time problem of feature generation in the SIFT method. The improvement is achieved by region-based feature classification in the objects to be detected; optimal neural network-based feature reduction is presented in order to reduce the object region feature dataset with winner pixel estimation between the video frames of the video sequence. Simulation results show that the proposed scheme achieves better overall performance than other object detection techniques, and region-based feature detection is faster in comparison to other recent techniques.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.39-42
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• 2016

Since a display device such as TV or signage is getting larger, the types of media is getting changed into wider view one such as UHD, panoramic and jigsaw-like media. Especially, panoramic and jigsaw-like media is realized by stitching video clips, which are captured by different camera or devices. In order to stich those video clips, it is required to find out 2D Adjacency Matrix, which tells spatial relationships among those video clips. Discrete Cosine Transform (DCT), which is used as a compression transform method, can convert the each frame of video source from the spatial domain (2D) into frequency domain. Based on the aforementioned compressed features, 2D adjacency Matrix of images could be found that we can efficiently make the spatial map of the images by using DCT. This paper proposes a new method of generating 2D adjacency matrix by using DCT for producing a panoramic and jigsaw-like media through various individual video clips.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.375-378
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• 2005

The multi-view video is a collection of multiple videos capturing the same scene at different viewpoints. The multi-view video can be used in various applications, including free viewpoint TV and three-dimensional TV. Since the data size of the multi-view video linearly increases as the number of cameras, it is necessary to compress multi-view video data for efficient storage and transmission. The multi-view video can be coded using the concept of the layered depth image (LDI). In this paper, we describe a procedure to generate LDI from the natural multi-view video and present a method to encode multi-view video using the concept of LDI.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.408-411
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• 2004

Color filter is a fundamental and necessary component to make a full-color TFT-LCD, its quality intensively influence the performance of TFT-LCD in the application of Notebook Computer, Monitor and Television. Color filter in chromaticity also make an effect for human visual system and video enjoyment. Recently, mother glass size is enlarged for demand of large-size panels and new generation color .filter technology for large-size liquid crystal cell panels is also developed. Here, latest generation color filter technology in TFT-LCD will be discussed.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.713-725
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• 2014

Multi-view and 3D video technologies for a next generation video service are widely studied. These technologies can make users feel realistic experience as supporting various views. Because acquisition and transmission of a large number of views require a high cost, main challenges for multi-view and 3D video include view synthesis, video coding, and depth coding. Recently, JCT-3V (joint collaborative team on 3D video coding extension development) has being developed a new standard for multi-view and 3D video. In this paper, major tools adopted in this standard are introduced and evaluated in terms of coding efficiency and complexity. This performance analysis would be helpful for the development of a fast 3D video encoder as well as a new 3D video coding algorithm.