• Journal of Digital Convergence
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• v.10 no.9
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• pp.351-356
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• 2012

This paper presents the 2D/3D conversion technique using depth map which is generated based on the haze and relative height cue. In cases that only the conventional haze information is used, errors in image without haze could be generated. To reduce this kind of errors, a new approach is proposed combining the haze information with depth map which is constructed based on the relative height cue. Also the gray scale image from Mean Shift Segmentation is combined with depth map of haze information to sharpen the object's contour lines, upgrading the quality of 3D image. Left and right view images are generated by DIBR(Depth Image Based Rendering) using input image and final depth map. The left and right images are used to generate red-cyan 3D image and the result is verified by measuring PSNR between the depth maps.

• Proceedings of the Korea Society of Design Studies Conference
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• 2005.10a
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• pp.42-43
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• 2005

• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.207-213
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• 2004

The layered depth image (LDI) is an efficient approach to represent three-dimensional objects with complex geometry for image-based rendering (IBR). LDI contains several attribute values together with multiple layers at each pixel location. In this paper, we propose an efficient preprocessing algorithm to compress depth information of LDI. Considering each depth value as a point in the two-dimensional space, we compute the minimum distance between a straight line passing through the previous two values and the current depth value. Finally, the minimum distance replaces the current attribute value. The proposed algorithm reduces the variance of the depth information , therefore, It Improves the transform and coding efficiency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.1010-1019
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• 2013

Recently, research on hologram, which can realize perfect 3-dimensional imaging, becomes more active. But hologram has the defect that it costs a lot in generation. Thus, this paper proposes a method to generate a new digital hologram contents by manipulating the existing digital hologram contents. That is, this paper proposes the method to manipulating the digital hologram contents by manipulating and/or synthesizing the depth information to get a new digital hologram contents. The proposed methods have been experimented with various depth informations and digital hologram contents. For each kind of depth information, it has been manipulated for its position and distance. The result was converted to a digital hologram by the computer-generated hologram method and the resulting hologram was reconstructed.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.906-913
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• 2022

In this paper, we propose a new deep network architecture using nearest neighbor kernel for the estimation of dense depth map from its sparse map and corresponding color information. First, we propose to decompose the depth map signal into the structure and details for easier prediction. We then propose two separate subnetworks for prediction of both structure and details using classification and regression approaches, respectively. Moreover, the nearest neighboring kernel method has been newly proposed for accurate prediction of structure signal. As a result, the proposed method showed better results than other methods quantitatively and qualitatively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.763-774
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• 2015

Hand posture recognition has been a wide region of applications in Human Computer Interaction and Computer Vision for many years. The problem arises mainly due to the high dexterity of hand and self-occlusions created in the limited view of the camera or illumination variations. To remedy these problems, a hand posture recognition method using 3-D point cloud is proposed to explicitly utilize 3-D information from depth maps in this paper. Firstly, hand region is segmented by a set of depth threshold. Next, hand image normalization will be performed to ensure that the extracted feature descriptors are scale and rotation invariant. By robustly coding and pooling 3-D facets, the proposed descriptor can effectively represent the various hand postures. After that, SVM with Gaussian kernel function is used to address the issue of posture recognition. Experimental results based on posture dataset captured by Kinect sensor (from 1 to 10) demonstrate the effectiveness of the proposed approach and the average recognition rate of our method is over 96%.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.640-655
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• 2014

Many of today's video systems have additional depth camera to provide extra features such as 3D support. Thanks to these changes made in multimedia system, it is now much easier to obtain depth information of the video. Depth information can be used in various areas such as object classification, background area recognition, and so on. With depth information, we can achieve even higher coding efficiency compared to only using conventional method. Thus, in this paper, we propose the 2D video coding algorithm which uses depth information on top of the next generation 2D video codec HEVC. Background area can be recognized with depth information and by performing HEVC with it, coding complexity can be reduced. If current CU is background area, we propose the following three methods, 1) Earlier stop split structure of CU with PU SKIP mode, 2) Limiting split structure of CU with CU information in temporal position, 3) Limiting the range of motion searching. We implement our proposal using HEVC HM 12.0 reference software. With these methods results shows that encoding complexity is reduced more than 40% with only 0.5% BD-Bitrate loss. Especially, in case of video acquired through the Kinect developed by Microsoft Corp., encoding complexity is reduced by max 53% without a loss of quality. So, it is expected that these techniques can apply real-time online communication, mobile or handheld video service and so on.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.1093-1103
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• 2009

In this paper, we propose a new depth map based distributed multi-view video coding algorithm through an efficient side information generation. A distributed video coding scheme corrects errors between an original image and side information generated at a decoder by using channel coding techniques. Therefore, the more accurate side information is generated, the better performance of distributed video coding scheme is achieved. In the proposed algorithm, a distributed video coding scheme is applied to multi-view video coding based on depth map. Side information is also generated from images of adjacent views through 3D warping by using a depth map and is also combined with MCTI(motion compensated temporal interpolation) which uses images on a temporal axis, and 3D warping. Experimental results show that side information generated by using the proposed algorithm has 0.97dB better average PSNR compared with using MCTI and 3D warping separated. In addition, 8.01% of average bit-rate has been decreased while the same PSNR in R-D curves is kept.

• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.51-58
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• 2012

Recently, 3D technology based on depth image is widely used in various fields including 3D space recognition, image acquisition, interaction, and games. Depth camera is used in order to produce depth image, various types of effort are made to improve quality of the depth image. In this paper, we suggests using area-based Canny edge detector to improve depth image in applying 3D technology based on depth camera. The suggested method provides improved depth image with pre-processing and post-processing by fixing image quality deterioration, which may take place in acquiring depth image in a limited environment. For objective image quality evaluation, we have confirmed that the image is improved by 0.42dB at maximum, by applying and comparing improved depth image to virtual view reference software. In addition, with DSCQS(Double Stimulus Continuous Quality Scale) evaluation method, we are reassured of the effectiveness of improved depth image through objective evaluation of subjective quality.

• Journal of Information Display
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• v.10 no.1
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• pp.1-5
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• 2009

A novel computational integral imaging technique with enhanced depth sensitivity is proposed. For each lateral position at a given depth plane, the dissimilarity between corresponding pixels of the elemental images is measured and used as a suppressing factor for that position. The intensity values are aggregated to determine the correct depth plane of each plane object. The experimental and simulation results show that the reconstructed depth image on the incorrect depth plane is effectively suppressed, and that the depth image on the correct depth plane is reconstructed clearly without any noise. The correct depth plane is also exactly determined.