• 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 Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.97-124
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• 2012

This paper analyzes qualitatively the stereo 3D content factors causing viewer's discomfort. For this, we perform a subjective test that each subject strokes a specific key whenever he (she) feels discomfort during watching a stereo 3D contents. Also we extract the data for the factors in the 3D contents to obtain their quantitative values and the amounts of the temporal changes. Those two sets of data are used to analyze the contents to find the factors which cause viewer's discomfort. The factors to be considered are the amount and the frequency of the disparity changes, story of the contents, situation or environments of a scene, movement and the position of the camera, color and luminance information as well as disparities themselves. We analyse the various strong and weak factors and their composites to find how much discomfort each factor or composite causes. We also show the situations and their related factors that causes less discomfort than the amount of their disparities.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.31-43
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• 2014

A depth map is an important component for stereoscopic image generation. Since the depth map acquired from a depth camera has a low resolution, upsamling a low-resolution depth map to a high-resolution one has been studied past decades. Upsampling methods are evaluated by objective evaluation tools such as PSNR, Sharpness Degree, Blur Metric. As well, the subjective quality is compared using virtual views generated by DIBR (depth image based rendering). However, works on the analysis of the relation between depth map upsampling and stereoscopic images are relatively few. In this paper, we investigate the relationship between subjective evaluation of stereoscopic images and objective performance of upsampling methods using cross correlation and linear regression. Experimental results demonstrate that the correlation of edge PSNR and visual fatigue is the highest and the blur metric has lowest correlation. Further, from the linear regression, we found relative weights of objective measurements. Further we introduce a formulae that can estimate 3D performance of conventional or new upsampling methods.

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.362-371
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• 2014

Blur variation caused by camera de-focusing provides a proper cue for depth estimation. Depth from Defocus (DFD) technique calculates the blur amount present in an image considering that blur amount is directly related to scene depth. Conventional DFD methods use two defocused images that might yield the low quality of an estimated depth map as well as a reconstructed infocused image. To solve this, a new DFD methodology based on infocused and defocused images is proposed in this paper. In the proposed method, the outcome of Subbaro's DFD is combined with a novel edge blur estimation method so that improved blur estimation can be achieved. In addition, a saliency map mitigates the ill-posed problem of blur estimation in the region with low intensity variation. For validating the feasibility of the proposed method, twenty image sets of infocused and defocused images with 2K FHD resolution were acquired from a camera with a focus control in the experiments. 3D stereoscopic image generated by an estimated depth map and an input infocused image could deliver the satisfactory 3D perception in terms of spatial depth perception of scene objects.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.4
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• pp.37-45
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• 2000

In this paper we suggest a method of detecting the two eyes position of moving viewer by using images obtained through a color CCD camera, and also a method of rendering view-dependent 3D image which consists of depth estimation, image-based 3D object modeling and stereoscopic display process. Through the experiment of applying the suggested methods, we could find the accurate two-eyes position with the success rate of 97.5% within the processing time of 0.39 second using personal computer, and display the view-dependent 3D image using Fl6 flight model. And through the similarity measurement of stereo image rendered at z-buffer by Open Inventor and captured by stereo camera using robot, we could find that view-dependent 3D picture obtained by our proposed method is optimal to viewer.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.4
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• pp.15-20
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• 2010

The three dimensional information is extracted and visualized using by stereo images of the object and the method for a 3D stereoscopic image is presented by the vergence control algorithm. The matching, which is applied a undistortion of lens and the energy function, is executed for the efficient extraction three dimensional information. Especially, applying the optimized method of matched line to the multi direction of the disparity imges. The disadvantages of multi directional method and reliability expansion method is collected. The matched interesting range of the three dimensional information is visualized using by VRML and more 3D stereoscopic image is visualized through the vergence control according to distance of the object. more improved three dimensional information is provided to observer by visualizing both of them at the same time.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.6
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• pp.354-362
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• 2006

This paper suggests a method for generating high qualify stereo video avatar to support visual communication in a CAVE$^{TM}$-like system. In such a system because of frequent change of light projected onto screens around user, it is not easy to extract user silhouette robustly, which is an essential step to generate a video avatar. In this study, we use an infrared reflective image acquired by a grayscale camera with a longpass filter so that the change of visible light on a screen is blocked to extract robust user silhouette. In addition, using two color cameras positioned at a distance of a binocular disparity of human eyes, we acquire two stereo images of the user for fast generation and stereoscopic display of a high quality video avatar without 3D reconstruction. We also suggest a fitting algorithm of a silhouette mask on an infrared reflective image into an acquired color image to remove background. Generated stereo images of a video avatar are texture mapped into a plane in virtual world and can be displayed in stereoscopic using frame sequential stereo method. Suggested method have advantages that it generates high quality video avatar taster than 3D approach and it gives stereoscopic feeling to a user 2D based approach can not provide.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.293-295
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• 2013

최근 3D 비디오의 흥행과 더불어 사람들이 스테레오스코픽 비디오를 쉽게 접할 수 있게 되었다. 하지만 부적절한 스테레오 스코픽 비디오는 시청자로 하여금 어지럼증, 눈의 피로 등을 느끼게 할 수 있다. 따라서 비디오 컨텐츠를 분석하여 피로도를 예츨할 수 있는 지표의 개발이 필요하다. 스테레오스코픽 비디오에서 피로도를 유발시키는 원인은 여러 가지가 있으며, 본 논문에서는 비디오의 카메라 움직임 정보에 집중한다. 카메라의 흔들림은 심각한 멀미를 유발할 수 있다. 이는 스테레오스코픽 비디오에서 더욱 강렬하게 나타나게 된다. 우리는 스테레오스코픽 비디오의 흔들림을 측정하기 위해 3D 복원 기술을 사용한다. 특히, 좌안 비디오와 우안 비디오의 정보를 모두 활용하는 최적화된 알고리즘을 제안한다. 이를 통해 우리는 각 프레임의 카메라 위치와 방향 정보를 획득할 수 있다. 마지막으로 획득한 3차원 카메라 움직임 정보로부터 카메라의 흔들림을 잘 표현할 수 있는 점수를 계산한다.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.3
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• pp.365-370
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• 2004

Simultaneous measurement with PLIF(Planar Laser-Induced Fluorescence) and Stereo-PIV(Stereo Particle Image Velocimetry) was performed to investigate the structural characteristics of flow field in Rushton Turbine Mixer. Instantaneous 3D velocity fields are measured by two 2K${\times}$2K CCD cameras focused on an object plane with the angular displacement methods while the concentration fields are obtained through the measurement of the fluorescence intensity of Rhodamine B tracer excited by the second pulse of Nd:Yag laser light. Image distortion due to the camera view-angle is compensated by a mapping function. Finally, the spatial structures of turbulent flow around Rushton turbine were identified by the calculation of synchronized data of the velocity field and concentration field.

• Journal of Sensor Science and Technology
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• v.7 no.6
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• pp.418-425
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• 1998

Stereo cameras are the most widely used sensing systems for automated machines including robots to interact with their three-dimensional(3D) working environments. The position of a target point in the 3D world coordinates can be measured by the use of stereo cameras and the camera calibration is an important preliminary step for the task. Existing camera calibration techniques can be classified into two large categories - linear and nonlinear techniques. While linear techniques are simple but somewhat inaccurate, the nonlinear ones require a modeling process to compensate for the lens distortion and a rather complicated procedure to solve the nonlinear equations. In this paper, a method employing a neural network for the calibration problem is described for tackling the problems arisen when existing techniques are applied and the results are reported. Particularly, it is shown experimentally that by utilizing the function approximation capability of multi-layer neural networks trained by the back-propagation(BP) algorithm to learn the error pattern of a linear technique, the measurement accuracy can be simply and efficiently increased.