• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1C
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• pp.26-35
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• 2006

In this paper, an automatic mobile robot system for a intelligent path planning using the detection scheme of the spatial coordinates based on stereo camera is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity map obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation. From some experiments on robot driving with 240 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the mobile robot and the objects, and relative distance between the other objects is found to be very low value of $2.19\%$ and $1.52\%$ on average, respectably.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.42-52
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• 2010

The purpose of this study is to produce digital elevation model (DEM) in the Jebu tidal flat, one of the west coast of the Korean Peninsula, by means of photogrammetric techniques from aerial digital stereo-images. Produced DEM would be become the fundamental data for change detection of the sediment and erosion. To do so, epipolar line is established by relative orientation. Area-based matching is then carried out based on this line and matching size according to surface property of tidal flat after a classified image is produced from reflectance and texture of the surface. As the results, DEM generated by the proposed method showed subtle changes in height more precisely than DEM using the fixed matching size and DEM by the commercial S/W in the region, such as tidal flats having few level differences.

• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.185-195
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• 2004

This paper presents a multi-depth map fusion method for the 3D scene reconstruction. It fuses depth maps obtained from the stereo matching technique and the depth camera. Traditional stereo matching techniques that estimate disparities between two images often produce inaccurate depth map because of occlusion and homogeneous area. Depth map obtained from the depth camera is globally accurate but noisy and provide a limited depth range. In order to get better depth estimates than these two conventional techniques, we propose a depth map fusion method that fuses the multi-depth maps from stereo matching and the depth camera. We first obtain two depth maps generated from the stereo matching of 3-view images. Moreover, a depth map is obtained from the depth camera for the center-view image. After preprocessing each depth map, we select a depth value for each pixel among them. Simulation results showed a few improvements in some background legions by proposed fusion technique.

• Journal of IKEEE
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• v.28 no.1
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• pp.65-71
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• 2024

This paper proposes a neural network that can reduce the number of parameters while reducing matching errors in occluded regions to increase the accuracy of depth maps in stereo matching. Stereo matching-based object recognition is utilized in many fields to more accurately recognize situations using images. When there are many objects in a complex image, an occluded area is generated due to overlap between objects and occlusion by background, thereby lowering the accuracy of the depth map. To solve this problem, existing research methods that create context information and combine it with the cost volume or RoIselect in the occluded area increase the complexity of neural networks, making it difficult to learn and expensive to implement. In this paper, we create a depthwise seperable neural network that enhances regional feature extraction before cost volume generation, reducing the number of parameters and proposing a neural network that is robust to occlusion errors. Compared to PSMNet, the proposed neural network reduced the number of parameters by 30%, improving 5.3% in color error and 3.6% in test loss.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.514-523
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• 2004

In this paper, a new intelligent moving target tracking and surveillance system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time. Basing on these extracted data the pan/tilted-embedded stereo camera system is adaptively controlled and as a result, the proposed system can track the target adaptively under the various circumstance of the target. From some experiments using 80 frames of the test input stereo image, it is analyzed that standard deviation of the position displacement of the target in the horizontal and vertical directions after tracking is kept to be very low value of 1.82, 1.11, and error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 0.5% on average. From these good experimental results a possibility of implementing a new real-time intelligent stereo target tracking and surveillance system using the proposed scheme is finally suggested.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1025-1034
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• 2022

In this paper, we propose a post-processing method through interpolation of hole regions that occur when extracting point clouds. When image matching is performed on stereo image data, holes occur due to occlusion and building façade area. This area may become an obstacle to the creation of additional products based on the point cloud in the future, so an effective processing technique is required. First, an initial point cloud is extracted based on the disparity map generated by applying stereo image matching. We transform the point cloud into a grid. Then a hole area is extracted due to occlusion and building façade area. By repeating the process of creating Triangulated Irregular Network (TIN) triangle in the hall area and processing the inner value of the triangle as the minimum height value of the area, it is possible to perform interpolation without awkwardness between the building and the ground surface around the building. A new point cloud is created by adding the location information corresponding to the interpolated area from the grid data as a point. To minimize the addition of unnecessary points during the interpolation process, the interpolated data to an area outside the initial point cloud area was not processed. The RGB brightness value applied to the interpolated point cloud was processed by setting the image with the closest pixel distance to the shooting center among the stereo images used for matching. It was confirmed that the shielded area generated after generating the point cloud of the target area was effectively processed through the proposed technique.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.459-464
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• 2007

영상기반의 3자원 복원(reconstruction)에 대한 연구가 컴퓨터 성능의 발전과 다양한 영상기반의 복원 알고리즘의 연구로 인해 최근 좋은 결과를 보이고 있으나, 이는 얼굴영역과 같은 목적이 되는 영역이 각 입력영상으로부터 미리 정확하게 추출되어 있다고 가정하기 때문이다. 일반적으로 목적이 되는 영역을 추출하기 위해 차영상이 많이 이용되고 있지만 차영상은 잡음과 구멍(hole)과 같은 오 추출된 영역이 발생하기 때문에 목적이 되는 영역을 3차원으로 복원을 할 때 심각한 오류를 초래할 수 있다. 전경물체(목적이 되는 영역)을 정확하게 추출하기 위해 최근 그래프 컷(graph cut)을 이용한 방법이 다양하게 시도되고 있다. 그래프 컷은 데이터 항(data term)과 스무드 항(smooth term)으로 구성된 에너지 함수를 전역적으로 최소화하는 방법으로 여러 공학적 문제에서 좋은 결과를 보이고 있지만, 에너지 함수의 데이터 항을 설정할 때 필요한 사전정보를 자동으로 얻기가 어렵다. 스테레오 비전의 깊이 정보가 최근 전경 물체 추출을 위한 사전정보로 많이 이용되고 있고 그들의 실험환경에서는 좋은 결과를 보이지만, 3차원 얼굴 복원에서 얼굴의 대부분이 동질의 영역을 가지고 있기 때문에 깊이 정보를 구하기 어려워 정확한 사전정보를 구하기가 어렵다. 본 논문에서는 3차원 얼굴 복원을 효과적으로 하기 위한 그래프 컷 기반의 전경 물체 추출 방법을 제안한다. 에너지 함수의 데이터 항을 설정하기 위해 전경 물체에 대한 사전정보를 추출해야 하며, 이를 위해 차영상을 이용하여 대략적인 전경 물체 추출하고, 사전정보에 대한 오류를 줄이기 위해 잡음과 그림자 영역을 제거한다. 잡음과 그림자 영역을 제거하면 구멍이 발생하거나 실루엣이 손상되는 문제가 발생한다. 손상된 정보는 근접한 픽셀이 유사하지 않을 때 낮은 비용을 할당하는 에너지 함수의 스무드(smooth) 항에 의해 에지 정보를 기반으로 채워진다. 결론적으로 제안된 방법은 스무드 항과 대략적으로 설정된 데이터 항으로 구성된 에너지 함수를 그래프 컷으로 전역적으로 최소화함으로써 더욱 정확하게 목적이 되는 영역을 추출할 수 있다.

• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.487-497
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• 2013

In this paper, a method of using high resolution stereo images is proposed to efficiently detect DSM errors. Automatically generated DSMs from stereo matching can be a useful solution to acquire DSM data in various aspects but they may include many gross errors coming from automatic processing. Therefore, a method to detect the gross errors on DSM is required for efficient DSM update. In this paper, stereo analysis using high resolution stereo images was investigated to represent reliability of DSM grids. The analysis enabled automatic detection of the gross errors which greatly influenced DSM quality. We used the reference DSM to assess reliability of our proposed method. We confirmed from experimental results that our method can be a valuable DSM errors analysis for efficient DSM correction. Our method is useful to analyze and improve DSM accuracy for various types of DSM and DEM. It is expected that our approach can be exploited for achievement of reliable DSM and DEM.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.424-432
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• 2003

In this paper, an effective method of stereo image reconstruction through the regularized adaptive disparity estimation is proposed. Althougth the conventional adaptive disparity estimation method can sharply improve the PSNR of a reconstructed stereo image, but some problems of overlapping between the matching windows and disallocation of the matching windows can be occurred, because the matching window size changes adaptively in accordance with the magnitude of feature values. Accordingly, in thia paper, a new regularized adaptive disparity estimation technique is proposed. That is, by regularizing the estimated disparity vector with the neughboring disparity vectors, problems of the conventional adaptive disparity estimated scheme might be solved, and also the predicted stereo image can be more effectively reconstructed. From some experiments using the CCETT'S stereo image pairs of 'Man' and 'Claude', it is analyzed that the proposed disparity estimation scheme can improve PSNRs of the reconstructed images to 10.89dB, 6.13dB for 'Man' and 1.41dB, 0.81dB for 'Claude' by comparing with those of the conventional pixel-based and adaptive estimation method, respectively.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.429-436
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• 2005

A simple stereo matching algorithm using population-based incremental learning(PBIL) is proposed in this paper to decrease the general problem of genetic algorithms, such as memory consumption and inefficiency of search. PBIL is a variation of genetic algorithms using stochastic search and competitive teaming based on a probability vector. The structure of PBIL is simpler than that of other genetic algorithm families, such as serial and parallel ones, due to the use of a probability vector. The PBIL strategy is simplified and adapted for stereo matching circumstances. Thus, gene pool, chromosome crossover, and gene mutation we removed, while the evolution rule, that fitter chromosomes should have higher survival probabilities, is preserved. As a result, memory space is decreased, matching rules are simplified and computation cost is reduced. In addition, a scheme controlling the distance of neighbors for disparity smoothness is inserted to obtain a wide-area consistency of disparities, like a result of coarse-to-fine matchers. Because of this scheme, the proposed algorithm can produce a stable disparity map with a small fixed-size window. Finally, an alterative version of the proposed algorithm without using probability vector is also presented for simpler set-ups.