• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.439-448
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• 2020

In this paper, we propose a modified optimization algorithm for point cloud matching of multi-view RGB-D cameras. In general, in the computer vision field, it is very important to accurately estimate the position of the camera. The 3D model generation methods proposed in the previous research require a large number of cameras or expensive 3D cameras. Also, the methods of obtaining the external parameters of the camera through the 2D image have a large error. In this paper, we propose a matching technique for generating a 3D point cloud and mesh model that can provide omnidirectional free viewpoint using 8 low-cost RGB-D cameras. We propose a method that uses a depth map-based function optimization method with RGB images and obtains coordinate transformation parameters that can generate a high-quality 3D model without obtaining initial parameters.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.1
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• pp.159-166
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• 2004

Custom-tailored products are meant by the products having various sizes and shapes to meet the customer's different tastes or needs. Thus fabrication of custom-tailored products inherently involves inefficiency. To minimize this inefficiency, a new paradigm is proposed in this work. In this paradigm, different parts are grouped together according to their sizes and shapes. Then, representative shape of each group is derived and it will be used as the work-piece from which the parts in the group are machined. Once a new product is ordered, the optimal work-piece is selected through making similarity comparisons of new product and each representative shape. Then an effective NC tool-path is generated to machine only the different portions between the work-piece and the ordered product. The efficient machining conditions are also derived from this shape difference. By machining only the different portions between the work-piece and the ordered product, it saves time. Similarity comparison starts with the determination of the closest pose between two shapes in consideration. The closest pose is derived by comparing the ray distances while one shape is virtually rotated with respect to the other. Shape similarity value and overall similarity value calculated from ray distances are used for grouping. A prototype system based on the proposed methodology has been implemented and applied to the grouping and machining of the shoe lasts of various shapes and sizes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.70-73
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• 2003

Custom-tailored products are meant by the products having various sizes and shapes to meet the customer's different tastes or needs. Thus fabrication of custom-tailored products inherently involves inefficiency. To minimize this inefficiency, a new paradigm is proposed in this work. In this paradigm. different paris are grouped together according to their sizes and shapes. Then, representative shape of each group is derived and it will be used as the work-piece from which the parts in the group are machined. Once a new product is ordered, the optimal work-piece is selected through making similarity comparisons of new product and each representative shape. Then an effective NC tool-path is generated to machine only the different portions between the work-piece and the ordered product. The efficient machining conditions are also derived from this shape difference. By machining only the different portions between the work-piece and the ordered product, it saves time. Similarity comparison starts with the determination of the closest pose between two shapes in consideration. The closest pose is derived by comparing the ray distances while one shape is virtually rotated with respect to the other. Shape similarity value and overall similarity value calculated from ray distances are used for grouping. A prototype system based on the proposed methodology has been implemented and applied to the grouping and machining of the shoe lasts of various shapes and sizes.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.373-380
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• 2022

This paper considers a method of fast correspondence matching for iterative closest point (ICP) algorithm. In robotics, the ICP algorithm and its variants have been widely used for pose estimation by finding the translation and rotation that best align two point clouds. In computational perspectives, the main difficulty is to find the correspondence point on the reference point cloud to each observed point. Jump-table-based correspondence matching is one of the methods for reducing computation time. This paper proposes a method that corrects errors in an existing jump-table-based correspondence matching algorithm. The criterion activating the use of jump-table is modified so that the correspondence matching can be applied to the situations, such as point-cloud registration problems with highly curved surfaces, for which the existing correspondence-matching method is non-applicable. For demonstration, both hardware and simulation experiments are performed. In a hardware experiment using Hokuyo-10LX LiDAR sensor, our new algorithm shows 100% correspondence matching accuracy and 88% decrease in computation time. Using the F1TENTH simulator, the proposed algorithm is tested for an autonomous driving scenario with 2D range-bearing point cloud data and also shows 100% correspondence matching accuracy.

• Fashion & Textile Research Journal
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• v.23 no.6
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• pp.744-757
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• 2021

This study aims to develop a bodice and a jacket in 3D of the late 19th to early 20th based on the pattern drafting book of Gordon S. S., which contains body measurement method and pattern drafting system. The findings of this research are as follows. First, female tops of the late 19th to early 20th century are categorized as outer, jacket, vest, and bodice. Of these, this study highlights the jacket, which can be divided into 4 types: 4 kinds of basic jacket, 2 kinds of riding jacket, bolero jacket, and newmarket jacket. Second, by referring to Gordon's pattern drafting system and book, a bodice was developed in 3D format based on the adherence to the following steps: analysis of the pattern drafting system, pattern drafting, 3D virtual simulation, 3D virtual fitting analysis, and the pattern correction. A bodice pattern corrected by 3D virtual clothing simulation results was proposed. Last, a basic sleeve and collar pattern for a basic jacket was drafted, which was followed by the correction and transformation of the bodice pattern. The jacket developed shows great fit except for the issues at the armhole line and shoulder, which were caused by the unique shape of the sleeves(big sleeve head) of the time. The study attempted to develop the past costumes in 3D, providing the basis for interdisciplinary research in the field of fashion history field and suggesting a new approach for the virtual restoration of costumes. Future studies should target to 3D virtual simulation in accordance to the 3D avatar pose in the developed virtual costume.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.188-195
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• 2024

This paper proposes a photorealistic real-time dense 3D mapping system that utilizes a neural network-based image enhancement method and mesh-based map representation. Due to the characteristics of the underwater environment, where problems such as hazing and low contrast occur, it is hard to apply conventional simultaneous localization and mapping (SLAM) methods. At the same time, the behavior of Autonomous Underwater Vehicle (AUV) is computationally constrained. In this paper, we utilize a neural network-based image enhancement method to improve pose estimation and mapping quality and apply a sliding window-based mesh expansion method to enable lightweight, fast, and photorealistic mapping. To validate our results, we utilize real-world and indoor synthetic datasets. We performed qualitative validation with the real-world dataset and quantitative validation by modeling images from the indoor synthetic dataset as underwater scenes.

• Fashion & Textile Research Journal
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• v.15 no.6
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• pp.1000-1009
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• 2013

Well-fitting riding breeches provide a comfortable ride. Horse-riding breeches should fit the lower body with patches located on the inside of hip and knees to prevent tears and slips. This study provides information about the fit of women's breeches using 3D human body scan data wearing commercially available two breeches according to posture. To get information about breeches fit, we measured the angle of waist line, the length, and the area of the breeches fit on four 20's women. This research showed the problem which was down for waist back line in the case of the horseback riding pose. The back waistline of the riding breeches should be raised compared to the front waistline; subsequently, an increased waistline angle results in less back waistline decrease. The breeches have plenty of length from back waist to crotch so the breech fit can be improved. The thigh circumference increased when riding in the front; therefore, good elasticity of the weft direction of the fabric is recommended. The length increase and the peripheral increase of the front knee significantly increased the surface area of the knee; consequently, knee patch material should be a two-way elastic fabric in all directions to enhance comfort according to riding motion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1189-1204
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• 2018

Detecting and capturing 3D human structures from the intensity-based image sequences is an inherently arguable problem, which attracted attention of several researchers especially in real-time activity recognition (Real-AR). These Real-AR systems have been significantly enhanced by using depth intensity sensors that gives maximum information, in spite of the fact that conventional Real-AR systems are using RGB video sensors. This study proposed a depth-based routine-logging Real-AR system to identify the daily human activity routines and to make these surroundings an intelligent living space. Our real-time routine-logging Real-AR system is categorized into two categories. The data collection with the use of a depth camera, feature extraction based on joint information and training/recognition of each activity. In-addition, the recognition mechanism locates, and pinpoints the learned activities and induces routine-logs. The evaluation applied on the depth datasets (self-annotated and MSRAction3D datasets) demonstrated that proposed system can achieve better recognition rates and robust as compare to state-of-the-art methods. Our Real-AR should be feasibly accessible and permanently used in behavior monitoring applications, humanoid-robot systems and e-medical therapy systems.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.51-59
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• 2016

In this paper we present (1) analysis of imaging sonar measurement for two-view relative pose estimation of an autonomous vehicle and (2) bundle adjustment and 3D reconstruction method using imaging sonar. Sonar has been a popular sensor for underwater application due to its robustness to water turbidity and visibility in water medium. While vision based motion estimation has been applied to many ground vehicles for motion estimation and 3D reconstruction, imaging sonar addresses challenges in relative sensor frame motion. We focus on the fact that the sonar measurement inherently poses ambiguity in its measurement. This paper illustrates the source of the ambiguity in sonar measurements and summarizes assumptions for sonar based robot navigation. For validation, we synthetically generated underwater seafloor with varying complexity to analyze the error in the motion estimation.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.401-410
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• 2016

3D registration is a computer vision technique of aligning multi-view range images with respect to a reference coordinate system. Various 3D registration algorithms have been introduced in the past few decades. Iterative Closest Point (ICP) is one of the widely used 3D registration algorithms, where various modifications are available nowadays. In the ICP-based algorithms, the closest points are considered as the corresponding points. However, this assumption fails to find matching points accurately when the initial pose between point clouds is not sufficiently close. In this paper, we propose a new method to solve this problem using the 6D distance (3D color space and 3D Euclidean distances). Moreover, a color segmentation-based adaptive sampling technique is used to reduce the computational time and improve the registration accuracy. Several experiments are performed to evaluate the proposed method. Experimental results show that the proposed method yields better performance compared to the conventional methods.