• ETRI Journal
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• v.29 no.5
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• pp.649-654
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• 2007

In this paper, we propose a computational integral imaging reconstruction (CIIR) method using a round mapping model to improve the viewing quality of 3-D images. The proposed CIIR method can overcome the problem of non-uniformly reconstructed images caused by the conventional method. To show the usefulness of proposed method, some experiments are carried out and the results are presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2280-2286
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• 2012

In this paper, we propose a novel nonlinear 3D image correlator using a fast computational integral imaging reconstruction (CIIR) method. In order to implement the fast CIIR method, the magnification process was eliminated. In the proposed correlator, elemental images of the reference and target objects are picked up by lenslet arrays. Using these elemental images, reference and target plane images are reconstructed on the output plane by means of the proposed fast CIIR method. Then, through nonlinear cross-correlations between the reconstructed reference and the target plane images, the pattern recognition can be performed from the correlation outputs. Nonlinear correlation operation can improve the recognition of 3D objects. To show the feasibility of the proposed method, some preliminary experiments are carried out and the results are presented by comparing the conventional method.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.718-721
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• 2008

Novel computational integral imaging technique with enhanced depth sensitivity is proposed. For each lateral position at a given depth plane, the dissimilarity between corresponding pixels of the elemental images is measured and used as a suppressing factor for that position. Experimental and simulation results show that reconstructed depth image on the incorrect depth plane is effectively suppressed.

• Proceedings of the Optical Society of Korea Conference
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• 2007.07a
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• pp.259-260
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• 2007

In this paper, we propose a novel computational integral imaging reconstruction (CIIR) method using round-type mapping model. Proposed CIIP method can overcome problems of non-uniformly reconstructed images caused from the conventional method and improve the resoulution of 3-D images. To show the usefulness of the proposed method, both computational experiment and optical experiment are carried out and their results are presented.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1363-1366
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• 2009

A new recognition method is used to find the three-dimensional target object on integral imaging. For finding the location of a target image, amount of reconstructed reference image is needed. This method is giving accurate information of target image by correlated among reconstructed target images and reference images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.991-996
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• 2007

Recently, a computational reconstruction method using an integral imaging technique, which is a promise three-dimensional display technique, has been actively researched. This method is that 3-D images can be digitally reconstructed at the required output planes by superposition of all of the inversely enlarged elemental images by using a hypothetical pinhole array model. However, the conventional method mostly yields reconstructed images having a low-resolution, because there are some intensity irregularities with a grid structure at the reconstructed mage plane by using square-type elemental images. In this paper, to overcome this problem, we propose a novel computational integral imaging reconstruction (CIIR) method using round-type mapping model. Proposed CIIR method can overcome problems of non-uniformly reconstructed images caused from the conventional method and improve the resolution of 3-D images. To show the usefulness of the proposed method, both computational experiment and optical experiment are carried out and their results are presented.

• Journal of Information Display
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• v.10 no.1
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• pp.1-5
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• 2009

A novel computational integral imaging technique with enhanced depth sensitivity is proposed. For each lateral position at a given depth plane, the dissimilarity between corresponding pixels of the elemental images is measured and used as a suppressing factor for that position. The intensity values are aggregated to determine the correct depth plane of each plane object. The experimental and simulation results show that the reconstructed depth image on the incorrect depth plane is effectively suppressed, and that the depth image on the correct depth plane is reconstructed clearly without any noise. The correct depth plane is also exactly determined.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1598-1603
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• 2011

This paper describes an enhancement method for a computational pickup model. The conventional computational pickup model utilizes the ray-trace model and the pinhole model. The conventional model is very useful, however, it suffers from quality degradation of reconstructed images at long distances. To overcome the problem, we propose an accurate pickup model. The proposed model includes integration of the rays incoming to a sensor that generates a pixel, resulting in robustness on the Aliasing artifact. To show the effectiveness of the proposed method, experimental results are carried out. The results indicated that the proposed method is superior to the conventional method.

• Annual Conference on Human and Language Technology
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• 2004.10d
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• pp.181-188
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• 2004

대다수의 개방영역 자연어 질의응답 시스템은 답을 선택할 수 있는 개념영역을 미리 정의하고 있기 때문에 시스템이 준비하지 못한 범주의 개념을 묻는 질의문에 대해서는 올바른 응답을 생성하지 못하거나 예외 처리 방식으로 응답을 생성해 낸다. 본 논문에서는 전형적인 범주에 속하지 않는 명사 개념에 관한 질의문에 대해 범용적으로 대응할 수 있는 개방영역 자연어 질의응답 시스템을 제안한다. 제안하는 시스템은 상위 개념 명사구(Hypernym)에 포함되는 하위 개념의 명사구(Hyponym)들을 추출할 수 있는 일반적인 패턴들을 그 신뢰도와 함께 가지고 있다. 따라서 질의문이 임의의 명사구 개념을 요청할 때 정답의 후보들을 동적으로 생성되는 가상의 is-a 의미관계 사전으로부터 신뢰 순위로 정렬하여 추출해 낼 수가 있다. 제안하는 시스템은 "What 명사구 동사구" 형태의 질의문들 중에서 개체명 인식기나 시소러스를 이용하여 정답 후보를 손쉽게 생성할 수 있는 질의문을 배제한 실험용 질의문 집합을 이용한 실험에서 42%의 재현율을 보였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1171-1176
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• 2011

This paper describes an analysis on the relationship between elemental image size and object locations in the computational integral imaging reconstruction and in the pickup using a periodically-distributed lenslet array. A sparse sampling effect arises from a periodically-distributed lenslet array in the pickup of 3D objects. The relationship between elemental image size and object location is also reported. Based on the analysis, a method to eliminate the sparse sampling is proposed. To show the effectiveness of the proposed method, experimental results are carried out. It turns out that the theory works.