• Korean Journal of Computational Design and Engineering
• /
• v.5 no.3
• /
• pp.285-292
• /
• 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.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.7
• /
• pp.634-640
• /
• 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.

• Journal of the Ergonomics Society of Korea
• /
• v.24 no.2
• /
• pp.35-43
• /
• 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.

• Journal of Sasang Constitutional Medicine
• /
• v.19 no.2
• /
• pp.30-39
• /
• 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.

• Proceedings of the KSME Conference
• /
• 2001.06c
• /
• pp.152-157
• /
• 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.

• IE interfaces
• /
• v.24 no.2
• /
• pp.105-111
• /
• 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.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2002.11a
• /
• pp.121-126
• /
• 2002

This paper introduces a method that can get information for the movement of a spreader and skew in order to drive ALS(Automatic Landing System) in the crane used at the harbor. Some methods that use 3D laser scanner sensor or laser range finder to obtain the information in ALS are used presently. But these have some defects respectively in economical efficiency and performance. Therefore, to recover these defects, we propose a method acquiring the information for the movement of a spreader and skew using CCD camera for image processing and laser range finder

• International conference on construction engineering and project management
• /
• 2020.12a
• /
• pp.361-370
• /
• 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.

• Korean Journal of Construction Engineering and Management
• /
• v.10 no.1
• /
• pp.136-145
• /
• 2009

The objective of the Intelligent Excavation System (IES) is to recognize the work environment and produce work plan and automatically control the excavator through integrating sensor and robot technologies. This paper discusses one of the core technologies of IES development project, development of 3D work environment modeling. 3D laser scanner is used for 3-dimensional mathematical model that can be visualized in virtual space in 3D. This paper describes (1) how the most appropriate 3D imaging system has been chosen; (2) the development of user interface and customization of the s/w to control the scanner for IES project; (3) the development of the mobile station for the scanner; (4) and the algorithm for the automatic registration of laser scan segments for IES project. The development system has been tested on the construction field and lessons learned and future development requirements are suggested.

• Tunnel and Underground Space
• /
• v.25 no.1
• /
• pp.97-106
• /
• 2015

We must precisely investigate the mechanical characters of rock to design rock slope safely and efficiently. But the method of clinometer has some disadvantages. So, we need a new measurement that can replace the method of clinometer. In this study, we analyze the reliability of joint orientation measurements in rock slope using the 3D laser scanner and program Split-FX that is a point cloud data analysis software. We could acquire the 495 pieces joint data through the automatic extraction of features. And we confirmed that there were some errors occurred with ${\pm}4^{\circ}$ of dip and ${\pm}5^{\circ}$ of dip direction. Generally, the method of clinometer has ${\pm}5^{\circ}$ and ${\pm}10^{\circ}$ error ranges of the joint orientation(dip/dip direction) that are the results of the advance research. Therefore, we analyzed the method of 3D laser scanner, and it is found to be efficient, reliable. This method is expected to mend the disadvantages of Clinometer method.