• 한국CDE학회논문집
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• 제5권3호
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• pp.285-292
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• 2000

A new method for the 3D automatic registration of the multiple range images has been developed for the 3D scanners(non-contact coordinates measurement systems). In the existing methods, the user usually has to input more than 3 pairs of corresponding points for the iterative registration process. The major difficulty of the existing systems lies in that the input corresponding points must be selected very carefully because the optimal searching process and the registration results mostly depend upon the accuracy of the selected points. In the proposed method, this kind of difficulty is greatly mitigated even though it needs only 2 pairs of the corresponding input points. Several registration examples on the 3D measured data have been presented and discussed with the introduction to the proposed algorithm.

• 제어로봇시스템학회논문지
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• 제21권7호
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• pp.634-640
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• 2015

This paper proposes a novel three-dimensional mapping algorithm in Omni-Directional Vision SLAM based on a fisheye image and laser scanner data. The performance of SLAM has been improved by various estimation methods, sensors with multiple functions, or sensor fusion. Conventional 3D SLAM approaches which mainly employed RGB-D cameras to obtain depth information are not suitable for mobile robot applications because RGB-D camera system with multiple cameras have a greater size and slow processing time for the calculation of the depth information for omni-directional images. In this paper, we used a fisheye camera installed facing downwards and a two-dimensional laser scanner separate from the camera at a constant distance. We calculated fusion points from the plane coordinates of obstacles obtained by the information of the two-dimensional laser scanner and the outline of obstacles obtained by the omni-directional image sensor that can acquire surround view at the same time. The effectiveness of the proposed method is confirmed through comparison between maps obtained using the proposed algorithm and real maps.

• 대한인간공학회지
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• 제24권2호
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• pp.35-43
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• 2005

The purpose of this study is to suggest computer assisted neck-base's landmark identification algorithms and measurement extraction methods from three-dimensional human scan data. So we developed the algorithms for automatic identification of landmarks related to the neck-base types. The subjects were 58 women $18{\sim}24$ years of age. Their body were measured directly and indirectly by using camera and three-dimensional body scanner. They were measured during the months of October in 2001. Based on the characters of classified neck-base types, algorithms for the automatic identification of landmarks and methods of automatic measurement are developed. The three-dimensional automatic measuring program is made by $C^{++}$ language. Using this program, 4 landmarks are identified and 6 items are measured. In the verifying the precision of automatic measurement, the height measurements(cervicale, side neck point, front neck point) were relatively accurate, but neck-base width measurement was measured wide.

• 사상체질의학회지
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• 제19권2호
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• pp.30-39
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• 2007

1. Objectives The Face is an important standard for the classification of Sasang Constitution. We are developing 3D Automatic Face Recognition Apparatus(3D-AFRA) to analyse the facial characteristics. This apparatus show us 3D image and data of man's face and measure facial figure data. So we should examine the figure restoration error of 3D Automatic Fare Recognition Apparatus(3D-AFRA) in hardware Error Analysis. 2. Methods We scanned Face status by using 3D Automatic Face Recognition Apparatus(3D-AFRA). And also we scanned Face status by using laser scanner(vivid 9i). We compared facial shape data be restored by 3D Automatic Face Recognition Apparatus(3D-AFRA) with facial shape data that be restorated by 3D laser scanner. And we analysed the average error and the maximum error of two data. 3. Results and Conclusions In frontal face, the average error was 0.48mm. and the maximum error was 4.60mm. In whole face, the average error of was 0.99mm. And the maximum error was 6.64mm. In conclusion, We assessed that accuracy of 3D Automatic Face Recognition Apparatus(3D-AFRA) is considerably good.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.152-157
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• 2001

This paper is to model a 3D-shape product applying mathematically the data acquired from a 30 scanner and using an Automatic Design Program. The research studied in th reverse engineering up to now has been developed continuously and surprisingly. However, forming 3D-shape sol id models in CAE and CAM. based on the research, the study leaves much to be desired. Especially, analyses and studies reverse-designing automatically using measured data after manufacturing. Consequently, we are going to acquire geometric data using an 30 scanner in this study with which we will open a new field of reverse engineering by a program which can design a 3D-shape solid model in a CDA-based program automatically. Utilization of this program make it possible to minimize time in designing a product and establish a ADS(Automatic design system) program library to using all of the data from reverse engineering.

• 산업공학
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• 제24권2호
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• pp.105-111
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• 2011

Measurement protocols for hand anthropometry have been studied for ergonomic product design. The present study developed a 3D semi-automatic measurement protocol (3D-SAMP) which semi-automatically measures various hand dimensions using a 3D scanner. The 3D-SAMP was compared with the conventional direct measurement method (DMM) to examine its effectiveness. The 3D-SAMP consists of (1) fabricating a plaster cast of the hand, (2) placing landmarks on the plaster hand, (3) scanning the plaster hand with a 3D scanner, (4) identifying automatically the positions of the landmarks on the digital hand, and (5) extracting automatically hand anthropometric measurements (lengths, widths, thicknesses, and circumferences). An evaluation experiment conducted in the study found the 3D-SAMP preferred to the DMM in terms of reliability (the number of dimensions exceeding the variability criteria SD=2 mm and CV=5% : 3D-SAMP =2 and DMM=24) and ease of measurement (3D-SAMP=5.2 and DMM=4.3 out of 7). The 3D-SAMP can be applied to ergonomic design of a hand-held product.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2002년도 추계공동학술대회논문집
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• pp.121-126
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• 2002

이 논문은 항만에서 사용되는 크레인에 있어서 ALS(Automatic Landing System)를 위한 스프레더(spreader)의 이동정보 및 스큐각을 얻을 수 있는 방법을 소개 하고자 한다. 현재 사용되고 있는 ALS에서의 이동정보 획득방법은 3차원 laser scanner 일종인 모서리 감지기를 이용하거나, 다수의 레이저 거리미터기를 이용하는 방법이 주를 이루고 있다. 그러나 이러한 방법들은 경제성 면에서 그리고 성능면에서 각각 단점을 가진다 따라서 본 논문에서는 이러한 단점들을 개선하기 위해서 CCD 카메라를 이용한 영상처리와 레이저 거리 미터기를 이용하여 스프레더의 이동정도와 스큐각을 획득할 수 있는 방법을 제안한다.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.361-370
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• 2020

Automatic building material recognition has been a popular research interest over the past decade because it is useful for construction management and facility management. Currently, the extensively used methods for automatic material recognition are mainly based on 2D images. A terrestrial laser scanner (TLS) with a built-in camera can generate a set of coloured laser scan data that contains not only the visual features of building materials but also other attributes such as material reflectance and surface roughness. With more characteristics provided, laser scan data have the potential to improve the accuracy of building material recognition. Therefore, this research aims to develop a TLS-based building material recognition method by combining machine learning techniques. The developed method uses material reflectance, HSV colour values, and surface roughness as the features for material recognition. A database containing the laser scan data of common building materials was created and used for model training and validation with machine learning techniques. Different machine learning algorithms were compared, and the best algorithm showed an average recognition accuracy of 96.5%, which demonstrated the feasibility of the developed method.

• 한국건설관리학회논문집
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• 제10권1호
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• pp.136-145
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• 2009

'지능형 굴삭시스템 개발'은 센서기술, 로봇기술들을 융합하여 토공 작업환경을 인식하고 작업 계획을 수립하며 굴삭기를 자동 조정하여 토공작업을 자동화 하는 것을 목표로 한다. 본 연구는 지능형 굴삭시스템 개발을 위한 요소기술로서, 광대역 3D 레이저 스캐너를 이용하여 실제 토공 작업환경을 가상의 3차원 공간으로 재현할 수 있는 수학적 모델을 만드는 것이다. 이 연구에서는 광대역 3D 레이저 스캐너를 구동하기 위한 사용자 소프트웨어 및 사용자 인터페이스를 개발하였으며, 3D 레이저 스캐너의 차량 탑재 및 스캐닝 작업의 최적화를 위하여 모바일 3D 이미징 시스템을 개발하였다. 또한 실제 토공 작업환경을 대상으로 스캐닝 실험을 실시하여 스캔 데이터를 획득하였고, 이를 기반으로 각 스캔 데이터들 간의 자동 정합 알고리즘을 설계하였다. 본 연구에서 개발된 시스템은 향후 지능형 굴삭 로봇의 완전 자동화 시스템의 구현을 위하여 널리 활용될 수 있을 것으로 기대된다.

• 터널과지하공간
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• 제25권1호
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• pp.97-106
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• 2015

암반사면을 안전하고 효율적으로 설계하기 위해서는 암반의 역학적 특성을 정밀하게 조사하여야 한다. 하지만 현재 사용되고 있는 클리노미터를 이용한 절리 조사의 한계점으로 인해 이를 보완할 수 있는 새로운 측정법의 연구가 필요로 하고 있다. 그러므로 본 연구에서는 3D Laser Scanner와 점군 데이터 분석 소프트웨어 Split-FX를 이용하여 암반사면의 절리방향 측정의 신뢰성을 분석하였다. 절리면 자동추출 기능을 통하여 총 495개의 절리 데이터를 얻었으며, 동일 지역을 클리노미터를 이용하여 측정한 38개의 데이터와 비교하여 분석한 결과 경사는 ${\pm}4^{\circ}$, 경사방향은 ${\pm}5^{\circ}$의 편차를 가지는 것을 확인하였다. 이러한 측정결과는 선행 연구를 통해 알게 된 클리노미터의 조사자에 따른 경사/경사방향 오차범위 ${\pm}5^{\circ}/{\pm}10^{\circ}$에 속하기 때문에 3D Laser Scanner를 이용한 절리데이터 취득 및 분석은 기존의 조사법을 보완할 수 있는 효율적이고 신뢰성 있는 조사법이라고 분석되었다.