• ETRI Journal
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• v.27 no.3
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• pp.326-329
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• 2005

The MPEG-4 multiple auxiliary component (MAC) is a good mechanism to achieve one-stream stereoscopic video coding. However, there is no syntax or semantics for the residual texture data of the disparity-compensated image in the current MAC. Therefore, we propose a novel disparity-compensated coding method using the MAC for stereoscopic video. We also define a novel MAC semantics in MPEG-4 so as to support the proposed coding algorithm. The major difference between the existing and proposed coding methods using the MAC is the addition of the residual texture coding.

• JSTS:Journal of Semiconductor Technology and Science
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• v.12 no.2
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• pp.127-138
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• 2012

In this paper, we propose a real-time virtual re-convergence hardware platform especially to reduce the visual fatigue caused by stereoscopy. Our unique idea to reduce visual fatigue is to utilize the virtual re-convergence based on the optimized disparity-map that contains more depth information in the negative disparity area than in the positive area. Our virtual re-convergence hardware platform, which consists of image rectification, disparity estimation, depth post-processing, and virtual view control, is realized in real time with 60 fps on a single Xilinx Virtex-5 FPGA chip.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.499-500
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• 2011

Line Disparity Map[1]은 스테레오 영역기반 정합방법에서 블록단위의 영역이 아닌 라인의 기울기를 바탕으로 비교하기 때문에 실시간 스테레오 정합이 가능하다. 따라서 본 논문은 이러한 Line Disparity Map 알고리즘을 사용하여 단순히 관찰로만 사용되어 지는 입체현미경에 스테레오 비전을 기반으로 하는 3D 형상계측 시스템을 개발하여 사람이 손으로 측정하기 힘든 미세의 오브젝트를 측정하는 시스템을 개발하고자 한다.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1141-1142
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• 2008

For intelligent vehicles, recognizing the sounding is an important task. In this paper we propose an road area detection system. This system uses u-disparity and v-disparity map. v-disparity map is used to find the road area. u-disparity is used to cluster the area that is an object. The test results and overall system is discribed in this paper.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1887-1890
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• 2003

This paper presents a three-dimensional (3D) head pose estimation algorithm using the stereo image. Given a pair of stereo image, we automatically extract several important facial feature points using the disparity map, the gabor filter and the canny edge detector. To detect the facial feature region , we propose a region dividing method using the disparity map. On the indoor head & shoulder stereo image, a face region has a larger disparity than a background. So we separate a face region from a background by a divergence of disparity. To estimate 3D head pose, we propose a 2D-3D Error Compensated-SVD (EC-SVD) algorithm. We estimate the 3D coordinates of the facial features using the correspondence of a stereo image. We can estimate the head pose of an input image using Error Compensated-SVD (EC-SVD) method. Experimental results show that the proposed method is capable of estimating pose accurately.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.109-118
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• 2006

In this paper, we suggest the environment based disparity method that calculate the depth value of the objects from environment maps. This method using the disparity of the environment map can calculate the depth value from two environment map that acquire at different viewpoint. This method can decide the visibility of the object whether it is occluded others or not. Also, we can analogize the depth value of the object that does not relate the reference plane(in case of being in the air) and make three dimensional environment model using the proposed method

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.435-436
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• 2006

When working with multi-view images, imbalances between multi-view images occur a serious problem in multi-view video coding because they decrease the performance of disparity estimation. To overcome this problem, we propose inter-view balanced disparity estimation for multi-view video coding. In general, the imbalance problem can be solved by a preprocessing step that transforms reference images linearly. However, there are some problems in pre-processing such as the transformation of the original images. In order to obtain a balancing effect among the views, we perform block-based disparity estimation, which includes several balancing parameters.

• Journal of the Korean Home Economics Association
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• v.40 no.4
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• pp.59-71
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• 2002

This study investigated the self wrapping made possible through the anonymity of cuber-space. According to the analysis of the data, which were collected from the online for 2 days, 2,168 respondents were grouped into three types: Those maintaining the strong sense of identity achievement), 53.8%, those experiencing confusion(identity diffusion), 38.3%, and those losing the sense of identity(foreclosure), 7.9%. Among the general respondents, it was reported that the case of sex wrapping was 11.4%, that of occupation, 40.1%, and that of marital status, 60.6%. Specially 11.4% of the sex wrapper took heterogeneous gender identity, while 7% performed dual sex roles. The rate of gender wrapping of female respondents was higher than that of male ones, which reflects female respondents' longing for male sex. Self-disparity between cyber-space and virtual-space was related with the type of self-identity and gender-identity. The rate of self-disparity between cuber-space and virtual-space was 9%. If it occurred continuously, it may cause individual mental division and maladjustment.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.805-807
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• 2005

본 논문에서는 동적 계획법(dynamic programming)과 이미지 세그먼트(segment)를 이용한 새로운 스테레오 정합(stereo matching)기법을 제안한다. 일반적으로 동적 계획법(dynamic programming)은 빠르면서도 비교적 정확하고, 조밀(dense)한 disparity map을 얻을 수 있다. 그러나 경계(boundary)근처의 폐색지역(occlusion region)이나, 텍스쳐가 적은 모호한 영역에서는 잘못된 결과를 유도할 수 있다. 본 논문에서는 이러한 문제점들을 해결하기 위해 먼저 이미지를 아주 작은 영역으로 분할(over-segmentation)하고, 이런 작은 영역들이 비슷한 disparity를 가질 것이라고 가정한다. 다음으로 동적 계획법(dynamic programming)을 통해 정합을 수행한다. 여기서 계산비용(cost)은 기존의 정합윈도우 안에서 세그먼트 영역을 적용한 새로운 비용함수를 사용하며, 이 새로운 비용함수를 통해 정확도를 높인다. 마지막으로 동적 계획법을 통하여 얻어진 조밀한 disparity map을 세그먼트 영역들의 시각특성(visibility)과 유사도(similarity)를 이용하여 에러를 찾아내고, 세그먼트 정합을 통해 수정함으로 정확한 disparity map을 찾아낸다.

• Journal of the Optical Society of Korea
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• v.4 no.1
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• pp.25-29
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• 2000

Two different binocular cues are known for detecting motion in depth. One is disparity change in time and the other is inter-ocular velocity difference. Shioiri, Saisho and Yaguchi (1999) demon-strated that motion in depth can be seen based solely on inter-ocular velocity differences as well as on the disparity change in time. They used conditions in which either cue was minimized and measured performance based on motion in depth, finding better performance than chance level when either velocity cue or the disparity cue was almost isolated. However, there may have been influences from the cue minimized in each condition, since it was practically impossible to isolate perfectly either cue. I re-analyzed their data to examine whether the performance in the condition with disparity change and that in the condition with inter-ocular velocity difference were correlated. The result showed the correlation is very low and therefore, we can conclude that the visual system has two different mechanisms for motion in depth.