• Journal of the Korea Convergence Society
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• v.3 no.1
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• pp.13-17
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• 2012

In this paper, we propose method of generation of depth map using vanishing line and texture. vanishing line is generated by parallel lines in image. For generate vanishing line, show boundary of particular angle through Gabor Filter and extract line through Hough Transform. Initial Depth Map is estimated based on vanisihng line and combine Relative Depth map that generated using Texture Cue. The proposed algorithm advanced due to combine Initial Depth Map and Relative Depth Map.

• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.67-71
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• 2016

This paper addresses a problem of defocus map recovery from single image. We describe a simple effective approach to estimate the spatial value of defocus blur at the edge location of the image. At first, we perform a re-blurring process using Gaussian function with input image, and calculate a gradient magnitude ratio with blurring amount between input image and re-blurred image. Then we get a full defocus map by propagating the blur amount at the edge location. Experimental result reveals that our method outperforms a reliable estimation of depth map, and shows that our algorithm is robust to noise, inaccurate edge location and interferences of neighboring edges within input image.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.44-53
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• 2011

In this paper, we propose a 3D conversion algorithm of 2D video using depth layer partition method. In the proposed algorithm, we first set frame groups using cut detection algorithm. Each divided frame groups will reduce the possibility of error propagation in the process of motion estimation. Depth image generation is the core technique in 2D/3D conversion algorithm. Therefore, we use two depth map generation algorithms. In the first, segmentation and motion information are used, and in the other, edge directional histogram is used. After applying depth layer partition algorithm which separates objects(foreground) and the background from the original image, the extracted two depth maps are properly merged. Through experiments, we verify that the proposed algorithm generates reliable depth map and good conversion results.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.697-698
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• 2006

In this paper, we propose a new scheme to generate multi-view images using a depth-image-based rendering (DIBR) technique. In order to improve the quality of multi-view images at newly exposed areas during mesh-based rendering, we preprocess the depth map using a Gaussian smoothing filter. Previous algorithms apply a smoothing filter to the whole depth map even if the depth map is collapsed. After extracting objects from the depth map, we apply the smoothing filter to their boundaries. Finally, we cannot only maintain the depth quality, but also generate high quality multi-view images. Experimental results show that our proposed algorithm outperforms previous works and supports an efficient depth keying technique.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.549-552
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• 2005

This paper presents a 3D video content generation technique and system that uses the multi-view images and the depth map. The proposed uses 3-view video and depth inputs from the 3-view video camera and depth camera for the 3D video content production. Each camera is calibrated using Tsai's calibration method, and its parameters are used to rectify multi-view images for the multi-view stereo matching. The depth and disparity maps for the center-view are obtained from both the depth camera and the multi-view stereo matching technique. These two maps are fused to obtain more reliable depth map. Obtained depth map is not only used to insert a virtual object to the scene based on the depth key, but is also used to synthesize virtual viewpoint images. Some preliminary test results are given to show the functionality of the proposed technique.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.275-278
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• 2012

본 논문에서 2D-3D 자동 영상 변환을 위하여 2D 상으로부터 깊이 지도(depth map)을 생성하는 방법을 제안한다. 제안하는 방법은 보다 정확한 깊이 지도 생성을 위해 영상의 전경 깊이 지도(foreground depth map)와 배경 깊이 지도(background depth map)를 각각 생성 한 후 결합함으로써 보다 정확한 깊이 지도를 생성한다. 먼저, 전경 깊이 지도를 생성하기 위해서 라플라시안 피라미드(laplacian pyramid)를 이용하여 포커스/디포커스 깊이 지도(focus/defocus depth map)를 생성한다. 그리고 블록정합(block matching)을 통해 획득한 움직임 시차(motion parallax)를 이용하여 움직임 시차 깊이 지도를 생성한다. 포커스/디포커스 깊이 지도는 평탄영역(homogeneous region)에서 깊이 정보를 추출하지 못하고, 움직임 시차 깊이 지도는 움직임 시차가 발생하지 않는 영상에서 깊이 정보를 추출하지 못한다. 이들 깊이 지도를 결합함으로써 각 깊이 지도가 가지는 문제점을 해결하였다. 선형 원근감(linear perspective)와 선 추적(line tracing) 방법을 적용하여 배경깊이 지도를 생성한다. 이렇게 생성된 전경 깊이 지도와 배경 깊이 지도를 결합하여 보다 정확한 깊이 지도를 생성한다. 실험 결과, 제안하는 방법은 기존의 방법들에 비해 더 정확한 깊이 지도를 생성하는 것을 확인할 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.513-518
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• 2016

This paper presents a fast 3D mesh generation method using projection for line laser-based 3D scanners. The well-known method for 3D mesh generation utilizes convex hulls for 4D vertices that is converted from the input 3D vertices. This 3D mesh generation for a large set of vertices requires a lot of time. To overcome this problem, the proposed method takes (${\theta}-y$) 2D depth map into account. The 2D depth map is a projection version of 3D data with a form of (${\theta}$, y, z) which are intermediately acquired by line laser-based 3D scanners. Thus, our 2D-based method is a very fast 3D mesh generation method. To evaluate our method, we conduct experiments with intermediate 3D vertex data from line-laser scanners. Experimental results show that the proposed method is superior to the existing method in terms of mesh generation speed.

• Smart Media Journal
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• v.1 no.3
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• pp.29-35
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• 2012

A depth image-based rendering (DIBR) technique is one of the rendering processes of virtual views with a color image and the corresponding depth map. The most important issue of DIBR is that the virtual view has no information at newly exposed areas, so called dis-occlusion. In this paper, we propose an intermediate view generation algorithm using the Kinect depth camera that utilizes the infrared structured light. After we capture a color image and its corresponding depth map, we pre-process the depth map. The pre-processed depth map is warped to the virtual viewpoint and filtered by median filtering to reduce the truncation error. Then, the color image is back-projected to the virtual viewpoint using the warped depth map. In order to fill out the remaining holes caused by dis-occlusion, we perform a background-based image in-painting operation. Finally, we obtain the synthesized image without any dis-occlusion. From experimental results, we have shown that the proposed algorithm generated very natural images in real-time.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.875-880
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• 2013

When we generate 3D video that provides immersive and realistic feeling to users, depth information of the scene is essential. Since the resolution of the depth map captured by a depth sensor is lower than of the color image, we need to upsample the low-resolution depth map for high-resolution 3D video generation. In this paper, we propose a depth upsampling method using depth-discontinuity information. Using the high-resolution color image and the low-resolution depth map, we detect depth-discontinuity regions. Then, we define an energy function for the depth map upsampling and optimize it using the belief propagation method. Experimental results show that the proposed method outperforms other depth upsampling methods in terms of the bad pixel rate.