• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1895-1898
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• 2003

양안 입체 TV 에서는 3 차원 카메라의 시점거리에 따라 눈의 편안함과 3 차원 효과 사이에 대차 관계가 존재한다. 일반적으로 카메라 사이의 거리가 인간의 동공 사이의 거리인 65㎜ 일 때 최적의 효과를 낸다고 한다. 그러나 일반적인 방송용 화질의 상용 카메라는 렌즈 크기가 크기 때문에 이 거리를 맞춘 3 차원 카메라를 제작하기는 매우 어렵다. 그래서 보기 편한 양안입체 영상을 제공하기 위해서는 스테레오 카메라에서 얻은 영상을 조작하여 원하는 가상 시점에서의 영상으로 만들어 줄 필요가 있다. 본 논문에서는 먼저 적응적 다중 창틀 정합을 이용한 계층적 변이 추정을 사용하여 변이 지도를 추출하고, 이것을 이용하여 가상 시점에서의 영상을 합성했다. 다양한 스테레오 영상을 이용한 실험을 통해 제안된 기법의 타당성을 확인하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.94-95
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• 2016

스테레오 정합은 서로 다른 두 시점을 갖는 스테레오 영상으로부터 객체의 깊이값을 예측한다. 이 방법은 객체가 카메라로 부터 멀리 떨어질수록 두 시점 사이에 큰 변위차를 갖는 양안시차 특성을 이용해 깊이값을 구한다. 일반적으로 스테레오 정합은 촬영한 두 영상의 조명 변화 및 노출 정도가 같다는 조건으로 수행된다. 하지만 실내 또는 실외에서 실제로 영상을 촬영하면 조명 및 햇빛의 위치 그리고 카메라의 특성에 따라 촬영된 스테레오 영상의 밝기가 서로 달라지는 경우가 발생하게 된다. 이처럼 두 영상의 밝기차를 고려하지 않고 스테레오 정합을 하게 되면 정확한 깊이값을 예측하기 어렵다. 이러한 문제를 개선하기 위해 조명 변화에 강인한 ANCC (Adaptive Normalized Cross Correlation)가 제안되었다. 이 방법은 영상 속 화소들의 색상 모델을 이용해 조명변화의 영향을 받는 요소들을 제거함으로써 다양한 밝기변화 속에서도 안정적으로 스테레오 정합을 수행할 수 있도록 한다. 하지만 ANCC는 수행과정에서 각 화소마다 양방향 필터 (Bilateral Filter)가 적용되는 등 높은 복잡도를 갖는다는 단점이 있다. 본 논문에서는 기존의 ANCC 보다 복잡도가 낮으면서 밝기변화에도 안정적인 정합 결과를 갖기 위해 Census 변환의 이진 정보를 이용한 스테레오 정합 방법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.739-742
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• 2001

영상처리 기법을 이용하여 움직이는 물체를 추적하는 시스템은 많은 분야에 응용될 수 있다. 기존의 물체 추적 시스템에서 사용한 방법들은 최적의 특성을 지니고 있지만, 많은 계산량을 요구하는 단점이 있다. 또한 단안에 의한 영상의 경우 물체의 다양한 변화에 대한 예측과 추적이 어렵다. 따라서 본 논문에서는 양안에 의해 얻어진 스테레오 영상에 전이(translation)와 회전(rotation)에서의 예측이 어려운 단점을 보완한 블록 정합 알고리즘을 적용함으로써 실시간 물체의 변화의 추적능력을 지니면서도 그 계산량을 줄일 수 있는 추적 방법에 대하여 기술한다. 또한 히스토그램의 계수 변화를 이용함으로써 블록 정합 알고리즘에서의 탐색영역을 제한하도록 하여 불필요한 처리시간을 절약하는 효율적인 물체추적 시스템을 제안한다.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.75-85
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• 2013

To acquire depth information using stereo vision, it is required to find correspondence points between stereo image pair. Conventional stereo vision systems usually use two cameras to get disparity data. Therefore, conventional stereo matching methods cannot resolve the tradeoff problem between accuracy and precision with respect to the length of baseline. Besides, belief propagation method, which is being used recently, has a problem that matching performance is dependent on the fixed weight parameter ${\lambda}$. In this paper, we propose a modified belief propagation stereo matching technique based on multi-baseline stereo vision to solve the tradeoff problem. The proposed method calculates EMAD(extended mean of absolute differences) as local evidence. And proposed method decides weight parameter ${\lambda}$ adaptively to local texture information. The proposed method shows higher initial matching performance than conventional methods and reached optimum solution in less iteration. The matching performance is increased about 4.85 dB in PSNR.

• The KIPS Transactions:PartA
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• v.14A no.5
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• pp.301-308
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• 2007

This paper proposes high performance coprocessor architecture for real time dense disparity computation based on a phase-based binocular stereo matching technique called local weighted phase-correlation(LWPC). The algorithm combines the robustness of wavelet based phase difference methods and the basic control strategy of phase correlation methods, which consists of 4 stages. For parallel and efficient hardware implementation, the proposed architecture employs SIMD(Single Instruction Multiple Data Stream) architecture for each functional stage and all stages work on pipelined mode. Such that the newly devised pipelined linear array processor is optimized for the case of row-column image processing eliminating the need for transposed memory while preserving generality and high throughput. The proposed architecture is implemented with Xilinx HDL tool and the required hardware resources are calculated in terms of look up tables, flip flops, slices, and the amount of memory. The result shows the possibility that the proposed architecture can be integrated into one chip while maintaining the processing speed at video rate.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.517-526
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• 2008

Stereo vision is a fundamental method for measuring 3D structures by observing them from two cameras placed on different positions. In order to reconstruct 3D structures, it is necessary to create a disparity map from a pair of stereo images. To create a disparity map we compute the matching cost for each point correspondence and compute the disparity that minimizes the sum of the whole matching costs. In this paper, we propose a method to estimate a dense disparity map using region segmentation. We segment each scanline using region homogeneity properties. Using the segmented regions, we prohibit false matches in the stereo matching process. Disparities for pixels that failed in matching are filled by interpolating neighborhood disparities. We applied the proposed method to various stereo images of real environments. Experimental results showed that the proposed method is stable and potentially viable in practical applications.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.305-315
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• 2012

Color correction between two or multiple images is very crucial for the development of subsequent algorithms and stereoscopic 3D camera system. Even though various color correction methods are proposed recently, there are few methods for measuring the performance of these methods. In addition, when two images have view variation by camera positions, previous methods for the performance measurement may not be appropriate. In this paper, we propose a method of measuring color difference between corresponding images for color correction. This method finds matching points that have the same colors between two scenes to consider the view variation by correspondence searches. Then, we calculate statistics from neighbor regions of these matching points to measure color difference. From this approach, we can consider misalignment of corresponding points contrary to conventional geometric transformation by a single homography. To handle the case that matching points cannot cover the whole regions, we calculate statistics of color difference from the whole image regions. Finally, the color difference is computed by the weighted summation between correspondence based and the whole region based approaches. This weight is determined by calculating the ratio of occupying regions by correspondence based color comparison.

• Journal of Broadcast Engineering
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• v.4 no.1
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• pp.59-67
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• 1999

In this paper, we study two important topics in stereoscopic image communication system. One is a disparity estimation (DE) method to obtain the depth information of a scene at the transmitter and the other is an intermediate view reconstruction(IVR) method at the receiver. We propose a new DE method using an edge-preserving directional regularization technique. The proposed DE method smooths disparity vectors in smooth regions and preserves edges without over-smoothing problem. It provides better reconstructed stereoscopic images and improved coding efficiency than the existing regularization techniques. In addition. we propose a new IVR method using interpolation and extrapolation techniques. The proposed IVR method preserves edge regions as well as occlusion regions well. Thus. it gives better intermediate views than the existing IVR methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.5
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• pp.522-534
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• 2002

In this paper, we propose a new object tracking system using stereo images to improve the performance of the automatic object tracking system. The existing object tracking system has optimum characteristics, but it requires a lot of computation. In the case of the image with a single eye, the system is difficult to estimate and track for the various transformation of the object. Because the stereo image by both eyes is difficult to estimate the translation and the rotation, this paper deals with the tracking method, which has the ability to track the image for translation for real time, with block matching algorithm in order to decrease the calculation. The experimental results demonstrate the usefulness of proposed system with the recognition rate of 88% in the rotation, 89% in the translation, 88% in various image, and with the mean rate of 88.3%.