• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.12-18
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• 2012

Stereo correspondence is the central problem of stereo vision. In this paper, we propose a stereo matching scheme based on a genetic algorithm using a multi-resolution method and AD-Census. The proposed approach considers the matching environment as an optimization problem and finds the disparity by using a genetic algorithm And adaptive chronosome structure using edge pixels and crossover mechanism are employed in this technique. A cost function is composes of certain constraints whice are commonly used in stereo matching. AD-Census measure is applied to reduce disparity error. To increase the efficiency of process, we apply image pyramid method to stereo matching and calculate the initial disparity map at the coarsest resolution. Then initial disparity map is propagated to the next finer resolution, interpolated and performed disparity refinement using local feature vector. We valid our method not only reduces the search time for correspondence compared with conventional GA-based method but also ensures the validity of matching.

• Journal of IKEEE
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• v.17 no.4
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• pp.517-524
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• 2013

Stereo matching has been grabbing the attention of researchers because it plays an important role in computer vision, remote sensing and photogrammetry. Although most methods perform well with small size images, experiments applying them to large-scale data sets under uncontrolled conditions are still lacking. In this paper, we present an empirical study on stereo matching for large-scale high-resolution satellite images. A new method is studied to solve the problem of huge size and memory requirement when dealing with large-scale high resolution satellite images. Integrating the tiling technique with the well-known dynamic programming and coarse-to-fine pyramid scheme as well as using memory wisely, the suggested method can be utilized for huge stereo satellite images. Analyzing 350 points from an image of size of 8192 x 8192, disparity results attain an acceptable accuracy with RMS error of 0.5459. Taking the trade-off between computational aspect and accuracy, our method gives an efficient stereo matching for huge satellite image files.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.6
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• pp.543-551
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• 2015

In this study, a novel method for dimension measurement of large-scale moving objects using stereo camera with 2-degree of freedom (2-DOF) mechanism is presented. The proposed method utilizes both the advantages of stereo vision technique and the enlarged visibility range of camera due to 2-DOF rotary mechanism in measuring large-scale moving objects. The measurement system employs a stereo camera combined with a 2-DOF rotary mechanism that allows capturing separate corners of the measured object. The measuring algorithm consists of two main stages. First, three-dimensional (3-D) positions of the corners of the measured object are determined based on stereo vision algorithms. Then, using the rotary angles of the 2-DOF mechanism the dimensions of the measured object are calculated via coordinate transformation. The proposed system can measure the dimensions of moving objects with relatively slow and steady speed. We showed that the proposed system guarantees high measuring accuracy with some experiments.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.4
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• pp.212-222
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• 2003

The ability to efficiently and robustly recover accurate 3D terrain models from sets of stereoscopic images is important to many civilian and military applications. A stereo matching has been an important tool for reconstructing three dimensional terrain. However, there exist many factors causing stereo matching error, such as occlusion, no feature or repetitive pattern in the correlation window, intensity variation, etc. Among them, occlusion can be only resolved by true multi-image stereo. In this paper, we present multi-image stereo method using DEM fusion as one of efficient and reliable true multi-image methods. Elevations generated by all pairs of images are combined by the fusion process which accepts an accurate elevation and rejects an outlier. We propose three fusion schemes: THD(Thresholding), BPS(Best Pair Selection) and MS(Median Selection). THD averages elevations after rejecting outliers by thresholding, while BPS selects the most reliable elevation. To determine the reliability of a elevation or detect the outlier, we employ the measure of self-consistency. The last scheme, MS, selects the median value of elevations. We test the effectiveness of the proposed methods with a quantitative analysis using simulated images. Experimental results indicate that all three fusion schemes showed much better improvement over the conventional binocular stereo in natural terrain of 29 Palms and urban site of Avenches.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.55-62
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• 2019

The stereo geometry establishment based on the precise sensor modeling is prerequisite for accurate stereo data processing. Ground control points are generally required for the accurate sensor modeling though it is not possible over the area where the accessibility is limited or reference data is not available. For the areas, the relative orientation should be carried out to improve the geometric consistency between the stereo data though it does not improve the absolute positional accuracy. The relative orientation requires conjugate points that are well distributed over the entire image region. Therefore the automatic conjugate point extraction is required because the manual operation is labor-intensive. In this study, we applied the method consisting of the key point extraction, the search space minimization based on the epipolar line, and the rigorous outlier detection based on the RPCs (Rational Polynomial Coefficients) bias compensation modeling. We tested different parameters of window sizes for Kompsat-2 across track stereo data and analyzed the RPCs precision after the bias compensation for the cases whether the epipolar line information is used or not. The experimental results showed that matching outliers were inevitable for the different matching parameterization but they were successfully detected and removed with the rigorous method for sub-pixel level of stereo RPCs precision.

• Smart Media Journal
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• v.12 no.9
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• pp.134-141
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• 2023

In this paper, we propose a ToF-Stereo fusion sensor system for 3D space scanning that increases the recognition rate of 3D objects, guarantees object detection quality, and is robust to the environment. The ToF-Stereo sensor fusion system uses a method of fusing the sensing values of the ToF sensor and the Stereo RGB sensor, and even if one sensor does not operate, the other sensor can be used to continuously detect an object. Since the quality of the ToF sensor and the Stereo RGB sensor varies depending on the sensing distance, sensing resolution, light reflectivity, and illuminance, a module that can adjust the function of the sensor based on reliability estimation is placed. The ToF-Stereo sensor fusion system combines the sensing values of the ToF sensor and the Stereo RGB sensor, estimates the reliability, and adjusts the function of the sensor according to the reliability to fuse the two sensing values, thereby improving the quality of the 3D space scan.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.5
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• pp.226-232
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• 2001

The ability to efficiently and robustly recover accurate 3D terrain models from sets of stereoscopic images is important to many civilian and military applications. To develop an effective and practical terrain modeling system, we propose a new multi-image stereo method which detect unreliable elevations in DEM(Digital Elevation Map), and fuse several DEMs from multiple sources into an accurate and reliable results. This paper focuses on two key factors for generating robust 3D terrain models: the ability to detect unreliable elevation estimates and the ability to fuse the reliable elevations into a single optimal terrain model. We apply the self-consistency methodology to reconstruct accurate DEM from multi-image and show the method is more effective than the conventional stereo image 3D reconstruction method. Using photo-realistic simulator, four synthetic image are generated from ground truth DEM and orthoimage to evaluate the accuracy of the proposed method quantitatively.

• The Journal of the Korea Contents Association
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• v.1 no.1
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• pp.24-31
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• 2001

In The AV system, to produce a realistic sound effect is very difficult because the distance between stereo speakers is very narrow. Many signal processing method of widening the sound image for spatial impression have been studied. Most of the typical methods of widening the sound image are related to the phase shifting. but this method was not effective in the concrete wall structure with high reflectivity. In this paper, we proposed an effective method of extending stereo sound image using Precedence Effect and reflected sound. In experiments we confirmed the usefulness of the method for extending stereo sound image of a conventional AV system in wider listening area of a room.

• Journal of Sensor Science and Technology
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• v.33 no.2
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• pp.98-104
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• 2024

This study proposes a method to overcome the limited detection range of short-baseline stereo cameras (SBSCs). The proposed method includes two steps: (1) predicting an unscaled initial depth using monocular depth estimation (MDE) and (2) adjusting the unscaled initial depth by a scale factor. The scale factor is computed by triangulating the sparse visual keypoints extracted from the left and right images of the SBSC. The proposed method allows the use of any pre-trained MDE model without the need for additional training or data collection, making it efficient even when considering the computational constraints of small platforms. Using an open dataset, the performance of the proposed method was demonstrated by comparing it with other conventional stereo-based depth estimation methods.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.162-173
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• 2008

In this paper, we propose an effective stereo-view video coding method that considers stereo-view and displayer characteristics. Current many stereo video displayers are designed for not only stereo display but also conventional single view display. In these systems, the resolution of two input videos for a stereo mode is half of that of single view for compatibility with conventional single view video services. In this raper, we propose a stereo video codec to deal with both single view and stereo view services by encoding whole left image and down-sampled right image. However, direct disparity estimation is not possible between two views because the resolution of a left image is different from that of the corresponding right image. So, we propose a disparity estimation method to make use of full information of the left reference image without down-sampling. In experimental result, we achieved $0.5{\sim}0.8\;dB$ coding gain, compared with several conventional algorithms.