• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.5
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• pp.132-140
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• 2016

In this paper, we propose boundary-preserving stereo matching method based on adaptive disparity adjustment using confidence region detection. To find the initial disparity map, we compute data cost using the color space (CIE Lab) combined with the gradient space and apply double cost aggregation. We perform left/right consistency checking to sort out the mismatched region. This consistency check typically fails for occluded and mismatched pixels. We mark a pixel in the left disparity map as "inconsistent", if the disparity value of its counterpart pixel differs by a value larger than one pixel. In order to distinguish errors caused by the disparity discontinuity, we first detect the confidence map using the Mean-shift segmentation in the initial disparity map. Using this confidence map, we then adjust the disparity map to reduce the errors in initial disparity map. Experimental results demonstrate that the proposed method produces higher quality disparity maps by successfully preserving disparity discontinuities compared to existing methods.

• 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.

• The Journal of the Korea Contents Association
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• v.13 no.10
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• pp.62-70
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• 2013

DIBR(Depth Image Based Rendering) is a kind of view synthesis algorithm to generate images at free view points from the reference color image and its depth map. One of the main challenges of DIBR is the occurrence of holes that correspond to uncovered backgrounds at the synthesized view. In order to cover holes efficiently, two main approaches have been actively investigated. One is to develop preprocessing algorithms for depth maps or parallax maps to reduce the size of possible holes, and the other is to develop hole filling methods to fill the generated holes using adjacent pixels in non-hole areas. Most conventional preprocessing algorithms for reducing the size of holes are based on the smoothing process of depth map. Filtering of depth map, however, attenuates the resolution of depth map and generates geometric distortions. In this paper, we proposes a novel preprocessing algorithm for parallax map to improve the performance of hole-filling by avoiding the drawbacks of conventional methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.13-20
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• 2005

In this paper, we propose new smoothing filters, i.e., occluding patterns that can accurately correct disparities of occluded areas in the estimated disparity map. An image is composed of several layers and each layer presents similar disparity. Furthermore, the distribution of the estimated disparities has a specific direction around the boundary of the occlusion, and this distribution presents the different direction with respect to the left- and the right-based disparity map. However, typical smoothing filters, such as mean filter and median filter, did not take into account those characteristic. So, they can decrease some error, but they cannot guarantee the accuracy of the corrected disparity. On the contrary, occluding patterns can accurately correct disparities of occluded areas because they consider both the characteristic that occlusion occurs and the characteristic that disparities of the occlusion are ranged, from estimated disparity maps with respect to the left and the right images. We made experiments on occluding patterns with some real stereo image set, and as a result, we can correct disparities of occluded areas more accurately than typical smoothing filters did.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.3
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• pp.349-354
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• 2011

In this paper we propose a simple efficient stereo matching algorithm to recover sharp object boundaries and to obtain dense disparity map using new multiple line shape windows. To this end, we consider left-right consistency and unique constraint. From the experimental results it is found that the proposed algorithm is very good for obtaining sharp and dense disparity maps for stereo image pairs.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.163-173
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• 2013

We present a new computer vision technique which can detect unexpected or static vertical objects in road driving environment. We first obtain temporal and spatial difference images in each frame of a stereo video sequence. Using the difference images, we then generate VO and HO maps by improving the conventional V and H disparity maps. From the VO and HO maps, candidate areas of vertical obstacles on the road are detected. Finally, the candidate areas are merged and refined to detect vertical obstacles.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.65-73
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• 2017

In this paper, we propose a stereo matching method to improve the image quality at the hole and the disparity discontinuity regions. The stereo matching method extracts disparity map finding corresponding points between stereo image pair. However conventional stereo matching methods have a problem about the tradeoff between accuracy and precision with respect to the length of the baseline of the stereo image pair. In addition, there are hole and disparity discontinuity regions which are caused by textureless regions and occlusion regions of the stereo image pair. The proposed method extracts initial disparity map improved at disparity discontinuity and miss-matched regions using modified AD-Census-Gradient method and adaptive weighted cost aggregation. And then we conduct the disparity map refinement to improve at miss-matched regions, while also improving the accuracy of the image. Experimental results demonstrate that the proposed method produces high-quality disparity maps by successfully improving miss-matching regions and accuracy while maintaining matching performance compared to existing methods which produce disparity maps with high matching performance. And the matching performance is increased about 3.22(%) compared to latest stereo matching methods in case of test images which have high error ratio.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1C
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• pp.55-64
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• 2006

In this paper, a new web-based remote 3D imaging communication system employing an adaptive matching algorithm is suggested. In the proposed method, feature values are extracted from the stereo image pair through estimation of the disparity and similarities between each pixel of the stereo image. And then, the matching window size for disparity estimation is adaptively selected depending on the magnitude of this feature value. Finally, the detected disparity map and the left image is transmitted into the client region through the network channel. And then, in the client region, right image is reconstructed and intermediate views be synthesized by a linear combination of the left and right images using interpolation in real-time. From some experiments on web based-transmission in real-time and synthesis of the intermediate views by using two kinds of stereo images of 'Joo' & 'Hoon' captured by real camera, it is analyzed that PSNRs of the intermediate views reconstructed by using the proposed transmission scheme are highly measured by 30dB for 'Joo', 27dB for 'Hoon' and the delay time required to obtain the intermediate image of 4 view is also kept to be very fast value of 67.2ms on average, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.10
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• pp.1829-1834
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• 2006

In this raper in order to recover sharp object boundaries we propose a new efficient stereo matching algorithm in which window size is varied to the distance from the boundaries of object. To this end, the processing region is divided into small subregions with a same area and the disparities of the center pixels in the subregions are calculated using a area-based algorithm with multiple windows. From the this disparity map we can find the edges of the contracted objects. The disparities of original image are obtained using the gradient constraint that means the disparity of the center pixel is similar to the ones of the remaining pixels in the subregion. from the experimental results it is found that the proposed algorithm is very good for recovering sharp object boundaries compared to the similar different algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.119-122
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• 2011

The Stereo vision using belief propagation algorithm that has been studied recently yields good performance in disparity extraction. In this paper, BP algorithm is proved theoretically to high precision for a stereo matching algorithm. We derive disparity map from stereo image by using Belief Propagation (BP) algorithm and area-based matching algorithm. Two algorithms are compared using stereo images provided by Middlebury web site. Disparity map error rate decreased from 52.3% to 2.3%.