• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 추계학술대회 논문집 학회본부
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• pp.484-487
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• 1989

A fast stereo algorithm for 3D depth estimation is presented. We propose an on-line stereo matching technique, by which the flows of stereo image signals are dynamically controlled to satisfy the matching condition of intensity functionals. The disparity is rapidly estimated from the control of. the signal flows and 3D depth is determined from the disparity.

• 전자공학회논문지B
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• 제30B권6호
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• pp.59-66
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• 1993

Stereo vision is useful in obtaining three dimensional depth information from two images taken from different view points. Neural network modeling for stereo matching, the key step in stereo vision, is defined by an energy function satisfying with three constraints proposed by Marr and Poggio. Stereo matching is then carried out through the network to find minimum energy corresponding to the optimized solution of the problem. An algorithm for stereo matching using an analog neural network is presented here. The network can reduce errors in initial state an early iteration steps by adoption of continuous sigmoid function in stead of binary state. The experimental results show good matching performance for sparse random dot stereogram and real image.

• 전기전자학회논문지
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• 제26권4호
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• pp.686-692
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• 2022

본 논문에서는 스테레오 영상정합을 위하여 개선된 영역기반, 에너지 기반 알고리즘, 학습기반 구조의 정합 오류율을 비교하였다. 영역기반으로 census transform(CT), 에너지 기반으로 belief propagation(BP) 알고리즘을 선정하였다. 기존 알고리즘을 개선하고 모바일 시스템에서 스테레오 영상정합에 활용가능 하도록 임베디드 프로세서 환경에서 구현하였다. 비교 대상이 되는 학습기반의 경우에 도 적은 규모의 파라메터를 활용하는 신경망 구조를 채택하였다. 세 가지 정합방법의 오류율 비교를 위해 테스트 이미지로 Middlebury 데이터 세트 가운데 Tsukuba를 선정하고 정합 성능의 정확한 비교를 위해 비폐색, 불연속, 시차 오류율 등으로 세분화하였다. 실험 결과 CT 매칭의 오차율은 기존 알고리즘과 수정된 알고리즘으로 비교하였을 때 약 11% 성능 개선되었다. BP 매칭은 오류율에서 기존 CT 에 비하여 약 87% 우수하였다. 신경망을 이용한 학습기반과 비교 하였을 때 BP 매칭이 약 31% 우수함을 보였다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2012년도 추계학술대회
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• pp.52-53
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• 2012

Belief propagation (BP) is a commonly used global energy minimization algorithm for solving stereo matching problem in 3D reconstruction. However, it requires large memory bandwidth and data size. In this paper, we propose a novel memory-efficient algorithm of BP in stereo matching on the Graphics Processing Units (GPU). The data size and transfer bandwidth are significantly reduced by storing only a part of the whole message. In order to maintain the accuracy of the matching result, the local messages are reconstructed using shared memory available in GPU. Experimental result shows that there is almost an order of reduction in the global memory consumption, and 21 to 46% saving in memory bandwidth when compared to the conventional algorithm. The implementation result on a recent GPU shows that we can obtain 22.8 times speedup in execution time compared to the execution on CPU.

• 한국측량학회지
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• 제32권6호
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• pp.591-597
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• 2014

A wide variety of image application methods, such as aerial image, terrestrial image, terrestrial laser, and stereo image point are currently under investigation to develop three-dimensional 3D geospatial information. In this study, matching points, which are needed to build a 3D model, were examined under diverse weather conditions by analyzing the stereo images recorded by closed circuit television (CCTV) cameras installed in the U-City. The tests on illuminance and precipitation conditions showed that the changes in the number of matching points were very sensitively correlated with the changes in the illuminance levels. Based on the performances of the CCTV cameras used in the test, this study was able to identify the optimal values of the shutter speed and iris. As a result, compared to an automatic control mode, improved matching points may be obtained for images filmed using the data obtained through this test in relation to different weather and illuminance conditions.

• 한국정보과학회논문지:소프트웨어및응용
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• 제32권3호
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• pp.173-180
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• 2005

본 논문은 스테레오 정합(stereo matching)과 마칭큐브(marching cube)알고리즘을 통합하는 효과적인 알고리즘을 제안한다. 여러 각도에서 획득한 영상에 대해 스테레오 정합 기술을 적용하여 3차원 형상 데이타를 획득하고 카메라 외부 파라미터를 이용하여 결합하였다. 결합된 데이타를 영상 색인을 이용하여 메쉬로 재구성한 다음 각 점에 해당하는 법선벡터를 획득하고 메쉬 평탄화(mesh smooth)의 과정을 거쳐서 데이타를 부드럽게 처리하였다. 본 논문은 3차원 메쉬 재구성에 대한 일련의 과정 및 기술을 서술하였으며, 기존의 마칭큐브 알고리즘에서 생기는 3차원 데이타의 불안정에 대한 문제를 중간 등위면(iso-surface) 알고리즘을 제안하여 개선하였다.

• Journal of Electrical Engineering and Technology
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• 제10권5호
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• pp.2189-2196
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• 2015

Stereo matching algorithm is usually used to obtain a disparity map from a pair of images. However, the disparity map obtained by using stereo matching contains lots of noise and error regions. In this paper, we propose a virtual-view synthesis algorithm using disparity refinement in order to improve the quality of the synthesized image. First, the error region is detected by examining the consistency of the disparity maps. Then, motion information is acquired by applying optical flow to texture component of the image in order to improve the performance. Then, the occlusion region is found using optical flow on the texture component of the image in order to improve the performance of the optical flow. The refined disparity map is finally used for the synthesis of the virtual view image. The experimental results show that the proposed algorithm improves the quality of the generated virtual-view.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2011년도 제43차 동계학술발표논문집 19권1호
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• pp.59-62
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• 2011

A new method is proposed for stereo vision where solution to disparity map is presented in terms of Line constraint and Reliability space -- the first constraint proposes a progressive framework for stereo matching which applies local area pixel-values from corresponding lines in the left and right image pairs. The second states that reliability space based on corresponding points records the disparity and then we are able to apply the median filter in order to reduce the noises which occur in the process. A coarse to fine result is presented after the median filtering, which improves the final result qualitatively. Experiment is evaluated by rectified stereo matching images pairs from Middlebury datasets and has proved that those two adopted strategies yield good matching quantitative results in terms of fast running speed.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권4호
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• pp.277-285
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• 2004

We present a new hybrid stereo matching technique in terms of the co-operation of area-based stereo and feature-based stereo. The core of our technique is that feature matching is carried out by the reference of the disparity evaluated by area-based stereo. Since the reference of the disparity can significantly reduce the number of feature matching combinations, feature matching error can be drastically minimized. One requirement of the disparity to be referenced is that it should be reliable to be used in feature matching. To measure the reliability of the disparity, in this paper, we employ the self-consistency of the disunity Our suggested technique is applied to the detection of 3D line segments by 2D line matching using our hybrid stereo matching, which can be efficiently utilized in the generation of the rooftop model from urban imagery. We carry out the experiments on our hybrid stereo matching scheme. We generate synthetic images by photo-realistic simulation on Avenches data set of Ascona aerial images. Experimental results indicate that the extracted 3D line segments have an average error of 0.5m and verify our proposed scheme. In order to apply our method to the generation of 3D model in urban imagery, we carry out Preliminary experiments for rooftop generation. Since occlusions are occurred around the outlines of buildings, we experimentally suggested multi-image hybrid stereo system, based on the fusion of 3D line segments. In terms of the simple domain-specific 3D grouping scheme, we notice that an accurate 3D rooftop model can be generated. In this context, we expect that an extended 3D grouping scheme using our hybrid technique can be efficiently applied to the construction of 3D models with more general types of building rooftops.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 춘계학술대회 논문집 센서 박막재료 반도체 세라믹
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• pp.194-199
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• 2003

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The proposed neural network technique is the real time computation method based theory of inter-node diffusion for searching the safety distances from the sudden appearance-objects during the work driving. The main steps of the distance computation using the theory of stereo vision like the eyes of man is following steps. One is the processing for finding the corresponding points of stereo images and the other is the interpolation processing of full image data from nonlinear image data of objects. All of them request much memory space and time. Therefore the most reliable neural-network algorithm is derived for real-time matching of objects, which is composed of a dynamic programming algorithm based on sequence matching techniques.