• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.487-489
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• 2001

본 논문은 구형 영상기반 가상환경에서 하나의 시점 영상 내에 포함되어 있는 임의의 물체를 모델링하여 3차원 운동이 가능한 시스템을 소개한다. 본 논문에서는 카메라 보정을 하지 않고, 물체에 대한 최소한의 기하학적 정보만을 이용하여 물체를 모델링하고, 모델링된 물체의 영상 기반 운동(image-based motion)의 가능성을 제시한다. 구현된 시스템은 구 환경에서의 하나의 시점 영상을 사영평면으로 간주하고 사용자에 의해 입력된 선과 점으로 투영된 3차원 물체의 2차원 모양을 모델링한다. 그리고 소실점을 이용해서 모델링된 입방체의 3차원 운동을 다룬다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1096-1101
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• 2004

The 3-D shape use to effect of movie, animation, industrial design, medical treatment service, education, engineering etc.... But it's not easy to make 3-D shape from the information of 2-D image. There are two methods in restoring 3-D video image through 2-D image; First the method of using a laser; Secondly the method of acquiring 3-D image through stereo vision. Instead of doing two methods with many difficulties, I figure out the method of simple 3-D image in this research paper. We present here a simple and efficient method, called direct calibration, which doesn't require any equations at all. The direct calibration procedure builds a lookup table(LUT) linking image and 3-D coordinates by a real 3-D triangulation system. The LUT is built by measuring the image coordinates of a grid of known 3-D points, and recording both image and world coordinates for each point; the depth values of all other visible points are obtained by interpolation.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.411-418
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• 2018

This paper presents a novel three-dimensional (3D) object encryption scheme by combining the use of the virtual optics and the chaotic sequence. A virtual 3D object is digitally produced using a two-dimensional (2D) elemental image array (EIA) created with a virtual pinhole array. Then, through a logistic mapping of chaotic sequence, a final encrypted video can be produced. Such method converts the value of a pixel which is the basic information of an image. Therefore, it gives an improved encryption result compared to other existing methods. Through computational experiments, we were able to verify our method's feasibility and effectiveness.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.205-212
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• 2019

Scene graph is a kind of knowledge graph that represents both objects and their relationships found in a image. This paper proposes a 3D scene graph generation model for three-dimensional indoor environments. An 3D scene graph includes not only object types, their positions and attributes, but also three-dimensional spatial relationships between them, An 3D scene graph can be viewed as a prior knowledge base describing the given environment within that the agent will be deployed later. Therefore, 3D scene graphs can be used in many useful applications, such as visual question answering (VQA) and service robots. This proposed 3D scene graph generation model consists of four sub-networks: object detection network (ObjNet), attribute prediction network (AttNet), transfer network (TransNet), relationship prediction network (RelNet). Conducting several experiments with 3D simulated indoor environments provided by AI2-THOR, we confirmed that the proposed model shows high performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.128-134
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• 2012

In this paper, we propose a novel approach to enhance the recognition performance of a far and partially occluded three-dimensional (3-D) target in computational curving-effective integral imaging (CEII) by using the direct pixel-mapping (DPM) method. With this scheme, the elemental image array (EIA) originally picked up from a far and partially occluded 3-D target can be converted into a new EIA just like the one virtually picked up from a target located close to the lenslet array. Due to this characteristic of DPM, resolution and quality of the reconstructed target image can be highly enhanced, which results in a significant improvement of recognition performance of a far 3-D object. Experimental results reveal that image quality of the reconstructed target image and object recognition performance of the proposed system have been improved by 1.75 dB and 4.56% on the average in PSNR (peak-to-peak signal-to-noise ratio) and NCC (normalized correlation coefficient), respectively, compared to the conventional system.

• KSCI Review
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• v.14 no.1
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• pp.241-248
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• 2006

The recognition of a relatively big and rarely movable object. such as refrigerator and air conditioner, etc. is necessary because these objects can be crucial global stable features of Simultaneous Localization and Map building(SLAM) in the indoor environment. In this paper. we propose a novel method to recognize these big objects using a sequence of 3D scenes. The particles representing an object to be recognized are scattered to the environment and then the probability of each particles is calculated by the matching test with 3D lines of the environment. Based on the probability and degree of convergence of particles, we can recognize the object in the environment and the pose of object is also estimated. The experimental results show the feasibility of incremental object recognition based on particle filtering and the application to SLAM

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.19-26
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• 2004

In this paper, we suggest a 3D vision inspection method which use only one camera. If we have the database of pattern and can recognize the object, and also estimate the rotated shape of the parts, we can inspect the parts using only one image. We used the 3D database and the 2D geometrical pattern matching, and the rotation transition theory about the algorithm. As the results, we could have the capability of the recognition and inspection of the rotated object through the estimation of rotation an81e. We applied our suggested algorithm to the inspection of typical IC and capacitor, and compared our suggested algorithm with the conventional 2D inspection method and the feature space trajectory method.

• Journal of the Korean Geophysical Society
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• v.7 no.4
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• pp.247-253
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• 2004

In this paper, 3D recognizing algorithm which is based on the external shape feature is presented. Since many objects have the regular shape, if we posses the database of pattern and we recognize the object using the database of the object's pattern, it is possible to inspect and/or recognize the objects of many fields. This paper handles on the 3D object recognition algorithm using the geometrical pattern matching by 3D database.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.10 no.4
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• pp.78-84
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• 1996

In this study, 3-D object recognition and restoration independent of the object translation for automotive kind recognition in parking administration system using an ultrasonic sensor array, neural networks and invariant moments are presented. Using invariant moment vectors of the acquired data 16$\times$8 pixels, 3-D objects could be classified by SCL (Simple Competitive Learning) neural networks. Modified SCL neural networks using the 16$\times$8 low resolution image was used for object restoration of 32$\times$32 high resolution image. Invariant moment vectors kept constant independent of the object translation. The recognition rates for the training and the testing data were 98[%] and 95[%], respectively. The experimental results have shown that ultrasonic sensor array with the neural networks could be applied for the detection of the automobiles and classification of the automotive kind.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.9B
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• pp.1251-1258
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• 2001

본 논문은 2차 다항식을 이용하여 3차원 물체의 표면 특징을 추출하고 표현하는 방법을 제안한다. 본 연구는 수정된 스캔 라인 기법을 이용하여 에지 맵을 얻는다. 에지 맵으로부터 3차원 물체의 각 면들을 분리하기 위해 레이블링 연산을 하고 각 면에서 중심점과 모서리 점들을 추출한다. 그 다음에, 평면 방정식으로부터 각 면이 평면인지 곡면인지를 판단한다. 3차원 물체를 표현하기 위해 각 면의 평면 또는 곡면의 계수 및 특징들을 추출한다. 합성영상과 실측영상을 통해서 제안된 기법의 성능을 알아보았고, 또한 제안된 기법으로 3차원 물체를 재구성하였다.