• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.107-113
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• 2016

Visual discomfort is a common problem in three-dimensional videos. Among the methods to overcome visual discomfort presented in current research, disparity adjustment methods provide little guidance in determining the condition for disparity control. We propose a diaprity adjustment based on the characteristics of disparity distribution on visual comfort, where the visual comfort level is used as the adjustment paramter, in parallax barrier type auto-stereoscopic 3D display. In this paper, we use the horizontal image shift method for disparity adjustment to enhance visual comfort. The speeded-up robust feature is used to estimate the disparity distribution of 3D sequences, and the required amount for disparity control is chosen based on the pre-defined characteristics of disparity distribution on visual comfort. To evaluate the performance of the proposed method, we used a 3D equipment. Subjective tests were conducted at the fixed optimal viewing distance. The results show that comfortable videos were generated based on the proposed disparity adjustment method.

• 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.

• Journal of the Optical Society of Korea
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• v.20 no.5
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• pp.633-640
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• 2016

In a dual lens stereoscopic camera, a convergence point determines the stereopsis effects of a video. When a user zooms an object, a convergence point is fixed since it is not coupled with a zoom function. Due to the fixed convergence point, it is possible for a zoom to cause the excessive binocular disparity resulting in visual discomfort. In this paper, to solve this problem, we build the relational model including all phenomena possible to arise and propose the adjustment methods of a convergence point by the positions of a focus, an object and a convergence point. We also evaluate the experiments measuring a binocular disparity and the subjective test to investigate the visual comfort. The results show that one of the proposed methods produced more comfortable 3D images to viewers than the others.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.349-360
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• 1995

This paper deals with the robustness properties of the minimum disparity estimation in linear regression models. The estimators defined as statistical quantities whcih minimize the blended weight Hellinger distance between a weighted kernel density estimator of the residuals and a smoothed model density of the residuals. It is shown that if the weights of the density estimator are appropriately chosen, the estimates of the regression parameters are robust.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.41-61
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• 2001

The minimum negative exponential disparity estimator(MNEDE), introduced by Lindsay(1994), is an excellenet competitor to the minimum Hellinger distance estimator(Beran 1977) as a robust and yet efficient alternative to the maximum likelihood estimator in parametric models. In this paper we define the negative exponential deviance test(NEDT) as an analog of the likelihood ratio test(LRT), and show that the NEDT is asymptotically equivalent to he LRT at the model and under a sequence of contiguous alternatives. We establish that the asymptotic strong breakdown point for a class of minimum disparity estimators, containing the MNEDE, is at least 1/2 in continuous models. This result leads us to anticipate robustness of the NEDT under data contamination, and we demonstrate it empirically. In fact, in the simulation settings considered here the empirical level of the NEDT show more stability than the Hellinger deviance test(Simpson 1989). The NEDT is illustrated through an example data set. We also define a goodness-of-fit statistic to assess adequacy of a specified parametric model, and establish its asymptotic normality under the null hypothesis.

• 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.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.452-455
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• 2007

3D stereoscopic viewing of large scale imagery, such as aerial photography and satellite images, needs different parallaxes relative to the display scale. For example, when a viewer sees a stereoscopic image of aerial photography, the optimal parallax of its zoom-in image should be smaller than that of its zoom-out. Therefore, relative parallax adjustment according to the display scale is required. Merely adjusting the spacing between stereo images is not appropriate because the depths of the whole image are either exaggerated or reduced entirely. This paper focuses on the improving stereoscopic viewing with a single remote sensing image and a digital surface model (DSM). We present the parallax adjustment technique to maximize the 3D realistic effect and the visual comfort. For remote sensing data, DSM height value can be regarded as disparity. There are two possible kinds of methods to adjust the relative parallax with a single image performance. One is the DSM compression technique: the other is an adjustment of the distance between the original image and its stereo-mate. In our approach, we carried out a test to evaluate the optimal distance between a single remote sensing image and its stereo-mate, relative to the viewing scale. Several synthetic stereo-mates according to certain viewing scale were created using a parallel projection model and their anaglyphs were estimated visually. The occlusion of the synthetic stereo-mate was restored by the inpainting method using the fields of experts (FoE) model. With the experiments using QuickBird imagery, we could obtain stereoscopic images with optimized parallax at varied display scales.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.49-54
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• 2024

Data imbalance is a common issue encountered in classification problems, stemming from a significant disparity in the number of samples between classes within the dataset. Such data imbalance typically leads to problems in classification models, including overfitting, underfitting, and misinterpretation of performance metrics. Methods to address this issue include resampling, augmentation, regularization techniques, and adjustment of loss functions. In this paper, we focus on loss function adjustment, particularly comparing the performance of various configurations of loss functions (Cross Entropy, Balanced Cross Entropy, two settings of Focal Loss: 𝛼 = 1 and 𝛼 = Balanced, Asymmetric Loss) on Multi-Class black-box video data with imbalance issues. The comparison is conducted using the I3D, and R3D_18 models.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.426-429
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• 2015

입체카메라에서 줌 사용시 컨버전스 포인트의 움직임에 따라 발생되는 시각적 불편의 문제와 거리감의 변동을 해결하기 위해 컨버전스 포인트 조정기법을 제시했었다. 본 연구에서는 이러한 조정기법의 우수성을 입증하기 위해 정량적 평가인 주시특성 분석을 설계했다. 입체영상에 대한 주관평가를 사용자의 시선움직임을 통해 정량적으로 파악하게 된다면 입체에 대한 사용자의 감성이미지를 보다 정확하게 파악할 수 있으며 이러한 자료를 통해 사용자 중심의 입체영상을 제작할 수 있는 환경을 제공하는 것이 가능할 것이다. 이를 통해 제시된 기법의 우수성을 정성과 정량적으로 입증한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.316-319
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• 2013

이안식 일체형 입체카메라는 줌인 시 고정된 컨버전스 포인트로 인해 촬영된 영상 시청할 때 어지러움을 유발하는 시각적 불편이 발생할 수 있다. 본 논문에서는 이안식 일체형 입체카메라에서 줌인 시 발생되는 시각적 불편을 방지하기 위해 제안된 컨버전스 포인트를 조정하는 기법을 실사로 촬영하고 각 기법 및 케이스별로 스테레오 분석을 실시한다. 이를 위해 포커스, 피사체 및 컨버전스 포인트의 위치에 따른 케이스와 각각의 간격 거리, 그리고 4가지 기법을 적용한 영상을 제작하여 스테레오 분석을 실시한다. 이로써 컨버전스 포인트를 조정하여 시각적 불편을 최소화하는 기법을 제안하고 제시한 깁법의 우수성을 입증한다.