• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.71-81
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• 2012

In order to support simple authoring an application of augmented reality for diverse users, the process for the object registration comprised of tracking and recognizing the object should be accomplished intuitively and simple. Although many 3D reconstruction methods to be applied to the object registration have been developed, the methods have not beyond the experimental level yet. In this paper, we proposed a novel marker-based tangible interfaces for various users to manipulate the object with intuitive and simple approaches during an authoring applications fo augmented reality. The proposed method make use of marker as intuitive interface to obtain 3D geometric information of 3D reconstruction. 3D geometric information of an object surface is acquired by touching the object directly with the proposed tangible interfaces. The tangible interfaces not only support 3D reconstruction for graphical modeling but also offer features information which is used for augmented reality. Finally, we verify efficiency of the proposed method with demonstration of an augmented reality application using the proposed method.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1682-1684
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• 2000

In this study, 3-D underwater object recognition using ultrasonic sensor fabricated with porous PZT-polymer 3-3 composites and SCL neural networks are presented. The recognition rates for the training data and the testing dara were 100 and 94.6% respectively.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.105-112
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• 1999

Image Processing Technique has been used as an efficient method to collect traffic information on the road such as vehicle counts, speed, queues, congestion and incidents. Most of the current methods which have been used to detect vehicles by the image processing are based on point processing, dealing with the local gray level of each pixel in the small window. However, these methods have some drawbacks. Firstly, detection is restricted by image quality. Secondly, they can not deal with occlusion and perspective projection problems, In this research, a new method which possibly deals with occlusion and perspective problems will be proposed. It extracts spatial information such as the position, the relationship of vehicles in 3-dimensional space, as well as vehicle detection in the image. The main algorithm used in this research is based on an extension of the Hough Transform. The Hough Transform which is proposed to estimates parameters of vertices and directed edges analytically on the Hough Space, is a valuable method for the 3-dimensional analysis of static scenes, motion detection and the estimation of viewing parameters.

• Korean Journal of Optics and Photonics
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• v.24 no.3
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• pp.120-124
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• 2013

We propose a method to reconstruct the two-dimensional object from an image captured through an array of random lenses each of which has random shape, size, and focal power. In the proposed method, the characteristics of the random lens array are estimated by capturing images for known elementary inputs, and then the object is reconstructed by measuring correlations between the random lens images of the object and the elementary inputs. The experimental results show that the original object can be recognized by the proposed reconstruction method. Nevertheless, further quality enhancement is required to increase feasibility and to extend to general three-dimensional object cases.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.560-562
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• 1999

The SOFM neural network as the recognizant algorithm of 3-D underwater object with ultrasonic sensor had the recognizant rate of 100%.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.6
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• pp.458-469
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• 1989

A measurement method is proposed which finds 3-D position and attitude of a known polyhedra utilizing shading information. Through the systematic interpretation of relations between polyhedra and its image as well as shadow image and also the determination of candidate position, 3-D information with respect to vertex of polyhedra is extracted. Following preprocessing of this information, the image of polyhedra is represented in terms of the scene with positioned object and the correspondence is searched by means of matching process between a scene description of the object and the correspondence is searched by means of matching process between a scene description of the object and a model description stored in data-base. In the experiments, initially 3-D information is employed to select several model regions, and objects are recognized through matching process with respect to scene regions. The results demonstrate that the recognition system performs with a high efficiency by proper selection of the threshold values.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.637-640
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• 2022

3차원 물체의 탐지와 자세 추정은 실내외 환경에서 장면 이해, 로봇의 물체 조작 작업, 자율 주행, 증강 현실 등과 같은 다양한 응용 분야들에서 공통적으로 요구되는 매우 중요한 시각 인식 기술이다. 깊이 지도를 요구하는 기존 연구들과는 달리, 본 논문에서는 RGB 컬러 영상만을 이용해 미지의 물체들, 즉 3차원 CAD 모델을 가지고 있지 않은 새로운 물체들을 탐지해내고, 이들의 자세를 추정해낼 수 있는 새로운 신경망 모델을 제안한다. 제안 모델에서는 최근 빠른 속도로 발전하고 있는 깊이 추정 기술을 이용함으로써, 깊이 측정 센서 없이도 물체 자세 추정에 필요한 깊이 지도를 컬러 영상에서 구해낼 수 있다. 본 논문에서는 벤치마크 데이터 집합을 이용한 실험을 통해, 제안 모델의 유용성을 평가한다.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.939-941
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• 1999

Recognition rates of 3-D underwater object using the SCL neural network and the SOFM neural network were 91.8% and 95.9%, respectively.

• Journal of the Korea Society of Computer and Information
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• v.6 no.2
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• pp.14-19
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• 2001

This paper presents a new method of 3-D surface feature extraction using a quadratic pol expression. With a range image, we get an edge map through the modified scan line technique this edge map, we label a 3-dimensional object to divide object's region and extract cent corner points from it's region. Then we determine whether the segmented region is a planar or a curved from the quadric surface equation. we calculate the coefficients of the planar su the curved surface to represent regions. In this article. we prove performance of the metho synthetic and real (Odetics) range images.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.500-503
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• 1997

In this paper, a method for recognizing 3-D objects using the 3-D Hough transform and the robust stereo vision is studied. A 3-D object is recognized through two steps; modeling step and matching step. In modeling step, features of the object are extracted by analyzing the IGES file. In matching step, the values of the sensed image are compared with those of the IGES file which is assumed to location and orientation in the 3-D Hough transform domain. Since we use the 3-D Hough transform domain of the input image directly, the sensitivity to the noise and the high computational complexity could be significantly allcv~ated. Also, the cost efficiency is improved using the robust stereo vision for obtaining depth map image which is needed for 3-D Hough transform. In order lo verify the proposed method, real telephone model is recognized. Thc results of the location and orientation of the model are presented.