• Journal of KIISE
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• v.41 no.11
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• pp.900-910
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• 2014

Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. The computational complexity of multi view video coding increases in proportion to the number of cameras. To reduce computational complexity and maintain the image quality, improved prediction structure and motion estimation method is proposed in this paper. The proposed prediction structure exploits an average distance between the current picture and its reference pictures. The proposed prediction structure divides every GOP into several groups to decide the maximum index of hierarchical B layer and the number of pictures of each B layer. And the proposed motion estimation method uses a hierarchical search strategy. This strategy method consists of modified diamond search pattern, progressive diamond search pattern and modified raster search pattern. Experiment results show that the complexity reduction of the proposed prediction structure and motion estimation method over JMVC (Joint Multiview Video Coding) reference model using hierarchical B pictures of Fraunhofer-HHI and TZ search method can be up to 40~70% while maintaining similar video quality and bit rates.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.495-502
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• 2013

Motion estimation (ME) that limits the performance of image quality and encoding speed has been developed to reduce temporal redundancy in video sequences and plays an important role in digital video compression. But it is computational demanding part of the encoder. Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. ME for Multi-view video requires high computational complexity. To reduce computational complexity and maintain the image quality, a fast motion estimation method is proposed in this paper. The proposed method uses a hierarchical search strategy. This strategy method consists of modified diamond search patten, multi gird diamond search pattern, and raster search pattern. These search patterns place search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum or exploits the characteristics of the distribution of motion vectors to place the search points. Experiment results show that the speedup improvement of the proposed method over TZ search method (JMVC) can be up to 1.2 ~3 times faster while maintaining similar video quality and bit rates.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.166-173
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• 2020

Multi-view images, which are widely used for providing free-viewpoint services, can enhance the quality of synthetic views when the number of views increases. However, there needs an efficient representation method because of the tremendous amount of data. In this paper, we propose a method for generating point cloud data for the efficient representation of multi-view color and depth images. The proposed method conducts sequential reconstruction of point clouds at each viewpoint as a method of deleting duplicate data. A 3D point of a point cloud is projected to a frame to be reconstructed, and the color and depth of the 3D point is compared with the pixel where it is projected. When the 3D point and the pixel are similar enough, then the pixel is not used for generating a 3D point. In this way, we can reduce the number of reconstructed 3D points. Experimental results show that the propose method generates a point cloud which can generate multi-view images while minimizing the number of 3D points.

• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.591-599
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• 2010

In this paper, we propose a disparity-adaptive filtering method to reduce view-aliasing and inter-perspective aliasing on auto-multiscopic 3D display. View aliasing by the subsampled multi-view images could happen if the resolution of an auto-multiscopic monitor is lower than that of the original multi-view images. Furthermore, multi-view images on auto-multiscopic monitor usually cause eye strain and fatigue because of inter-perspective aliasing by discontinuity that exists between viewpoints. The greater disparity value becomes, the stronger these types of aliasing could be. Thus, we design a lowpass filter whose cut-off frequency is determined adaptively to the number of intermediate reconstructed views and their disparity's strength. Though experimental results, we show that the proposed filtering algorithm could reduce the aliasing effect very efficiently by using DSCQS (double stimulus continuous quality scale method).

• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.55-64
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• 2010

This study tried to focus on nontraditional job that has not been studied in terms of the subjects associated with MSDs(Musculoskeletal Disorders). Specifically, dental procedure was the job to be analyzed in this study. An alternative method as well as a traditional method for viewing teeth while performing simulated dental procedures. Four graduated students did both methods(direct view and indirect view) as the subjects in this study. The method based on indirect view used a video camera and monitor to view the teeth. The experiment was conducted five times for each subject. The major findings in this study were as follows; 1) Job speed was increased with the repetitions for both methods, 2) Difference of Neck flexion between direct and indirect methods was statistically siginificant(Neck flexion for indirect method was dramatically decreased), 3) Difference of job speed between direct and indirect methods was statistically significant(Job speed for direct method was faster than that of indirect method), 4) Difference of error rate between direct and indirect methods was statistically significant(error rate for direct method was lower than that of indirect method), 5) Even though indirect method did not provide better performance in terms of job speed and error rate yet, it seemed to need a trade-off between two methods in the future since indirect method provided better working postures than that of direct method.

• Journal of Broadcast Engineering
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• v.12 no.4
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• pp.333-341
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• 2007

Multi-view video has recently gained much attraction from academic and commercial fields because it can deliver the immersive viewing of natural scenes. This paper presents multi-view video processing being composed of intermediate view reconstruction (IVR), graphics composition, and multi-view video viewer. First we generate virtual views between multi-view cameras using depth and texture images of the input videos. Then we mix graphic objects to the generated view images. The multi-view video viewer is developed to examine the reconstructed images and composite images. As well, it can provide users with some special effects of multi-view video. We present experimental results that validate our proposed method and show that graphic objects could become the inalienable part of the multi-view video.

• Journal of Fashion Business
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• v.19 no.2
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• pp.136-148
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• 2015

The purpose of this thesis is to study multi-view fashion design with an analysis of multi-view art's formation and philosophical perspective. The production of unique artwork is dependent on how we see, think and represent what is around us. Multi-view art has great potential as a concept related to the continuity of time and space, it is not limited to space and time but it extends to infinitely, according to the artist's will and imagination. The study of time and space has been used as principles for deriving the formative of multi-view art, and the principles applied for analyzing multi-view fashion design. And the formation of multi-view art is reflected in fashion design. Simultaneity, deconstructivity, continuity and virtuality in terms of multi-view art are support the formation of multi-view fashion design, such as fabrication, expandability, concealment and transparency. As such, it is important to study multi-view fashion design as a creative design method with immense potential for further development.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5546-5559
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• 2019

Facial action units (AUs) have recently drawn increased attention because they can be used to recognize facial expressions. A variety of methods have been designed for frontal-view AU detection, but few have been able to handle multi-view face images. In this paper we propose a method for multi-view facial AU detection using a fused multilayer, multi-task, and multi-label deep learning network. The network can complete two tasks: AU detection and facial view detection. AU detection is a multi-label problem and facial view detection is a single-label problem. A residual network and multilayer fusion are applied to obtain more representative features. Our method is effective and performs well. The F1 score on FERA 2017 is 13.1% higher than the baseline. The facial view recognition accuracy is 0.991. This shows that our multi-task, multi-label model could achieve good performance on the two tasks.

• Journal of the Optical Society of Korea
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• v.19 no.5
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• pp.477-486
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• 2015

We propose a novel calibration method which can be applied to all kinds of panel-type multi-view displays. We analyze how the angular, the axial, and the lateral misalignment affects the 3D image quality in a panel-type multi-view display. We demonstrate the ray optics simulation with a 3-view slanted parallax barrier system using pentile display for the quantitative calculation. Based on the analysis, we propose a new alignment pattern for all kinds of panel-type multi-view displays. The proposed pattern is sensitive to all of the angular, the axial, and the lateral misalignments. The high spatial frequency images and on and off alignment in the proposed pattern help observers to calibrate the system easily. We theoretically show the generality of the proposed alignment pattern and verify the pattern with image simulations and experiments.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.7
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• pp.53-61
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• 1998

In this paper, we propose an efficient multi-view images coding algorithm to find the optimal depth and texture from the set of multi-view images. The proposed algorithm consists of two consecutive steps, i) the depth estraction step, and ii) the texture extraction step, comparedwith the traditional algorithem which finds the depth and texture concurrently. The X-Y plane of the normalized object space is divided into traingular paatches and the Z value of the node is determined in the first step and then the texture of the each patch is extracted in the second step. In the depth extraction step, the depth of the node is determined by applying the block based disparity compensation method to the windowed area centered at the node. In the second step, the texture of the traingular patches is extracted from the multi-view images by applying the affine transformation based disparity compensation method to the traingular pateches with the depth extracted from the first step. Experimental results show that the SNR(Singnal-to- Noise Ratio) of images enconded by our algorithm is better than that of images encoded by the traditional algorithm by the amount about 4dB for for the test sets of multi-view images called dragon, kid, city and santa.