• Journal of Institute of Control, Robotics and Systems
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• v.7 no.2
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• pp.168-172
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• 2001

The accuracy problem of robot manipulators has long been one of the principal concerns in robot design and control. A practical and economical way of enhancing the manipulator accuracy, without affecting its hardware, is kinematic calibration. In this paper an effective and practical method is presented for kinematic calibration of Stewart platforms. In our method differential errors in kinematical parameters are linearly related to differential errors in the platform pose, expressed through the forward kinematics. The algorithm is tested using simulated measurement in which measurement noise is included.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.395-396
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• 2007

Bone age assessment has been widely used to measure the ossification in pediatric radiology. For the assessment, first bone age of each epiphyseal plate is estimated using DCT/LDA, then the bone age of a patient is calculated by using the median of 9 estimations. For some patients, however, due to various reasons such as X-ray image quality or the pose of fingers, it is common to miss couple of plates in automated systems. In this paper, we investigate the relationship between the number of detected plates and the accuracy of bone age assessment. In the experimental results, we confirmed the similarity between bone age assessed using more than 7 epiphyseal plates and that assessed using 9 epiphyseal plates.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.127-128
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• 2023

The construction industry is increasingly adopting vision AI technologies to improve efficiency and safety management. However, the complex and dynamic nature of construction sites can pose challenges to the accuracy of vision AI models trained on datasets that do not consider the background. This study investigates the effect of background on object recognition for vision AI in construction sites by constructing a learning dataset and a test dataset with varying backgrounds. Frame scaffolding was chosen as the object of recognition due to its wide use, potential safety hazards, and difficulty in recognition. The experimental results showed that considering the background during model training significantly improved the accuracy of object recognition.

• Journal of Biomedical Engineering Research
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• v.44 no.3
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• pp.167-175
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• 2023

Chest PA is the basic examination of radiographic imaging. Moreover, Chest PA's demands are constantly increasing because of the Increase in respiratory diseases. However, it is not meeting the demand due to problems such as a shortage of radiological technologist, sexual shame caused by patient contact, and the spread of infectious diseases. There have been many cases of using artificial intelligence to solve this problem. Therefore, the purpose of this research is to build an artificial intelligence dataset of Chest PA and to find a posture evaluation method. To construct the posture dataset, the posture image is acquired during actual and simulated examination and classified correct and incorrect posture of the patient. And to evaluate the artificial intelligence posture method, a posture estimation algorithm is used to preprocess the dataset and an artificial intelligence classification algorithm is applied. As a result, Chest PA posture dataset is validated with in over 95% accuracy in all artificial intelligence classification and the accuracy is improved through the Top-Down posture estimation algorithm AlphaPose and the classification InceptionV3 algorithm. Based on this, it will be possible to build a non-face-to-face automatic Chest PA examination system using artificial intelligence.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.108-114
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• 2015

Automated driving systems require a high level of performance regarding environmental perception, especially in urban environments. Today's on-board sensors such as radars or cameras do not reach a satisfying level of development from the point of view of robustness and availability. Thus, map data is often used as an additional data input to support these systems. An accurate digital map is used as a powerful additional sensor. In this paper, we propose a new approach for vehicle localization using a lane map and a single-layer LiDAR. The maps are created beforehand using a highly accurate DGPS and a single-layer LiDAR. A pose estimation of the vehicle was derived from an iterative closest point (ICP) match of LiDAR's intensity data to the lane map, and the estimated pose was used as an observation inside a Kalmanfilter framework. The achieved accuracy of the proposed localization algorithm is evaluated with a highly accurate DGPS to investigate the performance with respect to lateral vehicle control.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.262-268
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• 2017

Intelligent video surveillance systems have been developed to monitor global areas and find specific target objects using a large-scale database. However, person re-identification presents some challenges, such as pose change and occlusions. To solve the problems, this paper presents an improved person re-identification method using sparse representation and saliency-based dictionary construction. The proposed method consists of three parts: i) feature description based on salient colors and textures for dictionary elements, ii) orthogonal atom selection using cosine similarity to deal with pose and viewpoint change, and iii) measurement of reconstruction error to rank the gallery corresponding a probe object. The proposed method provides good performance, since robust descriptors used as a dictionary atom are generated by weighting some salient features, and dictionary atoms are selected by reducing excessive redundancy causing low accuracy. Therefore, the proposed method can be applied in a large scale-database surveillance system to search for a specific object.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.176-186
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• 1999

In order to produce an image that lends realism to audience in the virtual studio system. it is important to synchronize precisely between foreground objects and background image provided by computer graphics. In this paper, we propose a method of camera parameter extraction for the synchronization by tracking the pose of TV camera. We derive an equation for extracting camera parameters from inverse perspective equations for tracking the pose of the camera and 3-D transformation between base coordinates and estimated coordinates. We show the validity of the proposed method in terms of the accuracy ratio between the parameters computed from the equation and the real parameters that applied to a TV camera.

• Steel and Composite Structures
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• v.47 no.5
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• pp.615-631
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• 2023

Steel corrosion induces structural deterioration of concrete-filled steel tubes (CFSTs), and any potential extreme action on a corroded CFST would pose a severe threat. This paper presents a comprehensive investigation on the lateral impact behaviour of CFSTs suffering from localised pitting corrosion damage. A refined finite element analysis model is developed for the simulation of locally corroded CFSTs subjected to lateral impact loads, which takes into account the strain rate effects on concrete and steel materials as well as the random nature of corrosion pits, i.e., the distribution patterns and the geometric characteristics. Full-range nonlinear analysis on the lateral impact behaviour in terms of loading and deforming time-history relations, nonlinear material stresses, composite actions, and energy dissipations are presented for CFSTs with no corrosion, uniform corrosion and pitting corrosion, respectively. Localised pitting corrosion is found to pose a more severe deterioration on the lateral impact behaviour of CFSTs due to the plastic deformation concentration, the weakened confinement and the reduction in energy absorption capacity of the steel tube. An extended parametric study is then carried out to identify the influence of the key parameters on the lateral impact behaviour of CFSTs with localised pitting corrosion. Finally, simplified design methods considering the features of pitting corrosion are proposed to predict the dynamic flexural capacity of locally pitted CFSTs subjected to lateral impact loads, and reasonable accuracy is obtained.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.247-257
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• 2021

This paper proposes a new technique for calibrating a multi-view RGB-D camera using a 3D (dimensional) skeleton. In order to calibrate a multi-view camera, consistent feature points are required. In addition, it is necessary to acquire accurate feature points in order to obtain a high-accuracy calibration result. We use the human skeleton as a feature point to calibrate a multi-view camera. The human skeleton can be easily obtained using state-of-the-art pose estimation algorithms. We propose an RGB-D-based calibration algorithm that uses the joint coordinates of the 3D skeleton obtained through the posture estimation algorithm as a feature point. Since the human body information captured by the multi-view camera may be incomplete, the skeleton predicted based on the image information acquired through it may be incomplete. After efficiently integrating a large number of incomplete skeletons into one skeleton, multi-view cameras can be calibrated by using the integrated skeleton to obtain a camera transformation matrix. In order to increase the accuracy of the calibration, multiple skeletons are used for optimization through temporal iterations. We demonstrate through experiments that a multi-view camera can be calibrated using a large number of incomplete skeletons.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.4 s.304
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• pp.11-18
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• 2005

For expressing intention the human often use body languages as well as vocal languages. Of course the gestures using arms and hands are the representative ones among the body languages. Therefore it is very important to understand the human arm motion in human-computer interaction. In this respect we present here how to estimate 3D pose of human arms by using computer vision systems. For this we first focus on the idea that the human arm motion consists of mostly revolute joint motions, and then we present an algorithm for understanding 3D motion of a revolute joint using vision systems. Next we apply it to estimating 3D pose of human arms using vision systems. The fundamental idea for this algorithm extension is that we may apply the algorithm for a revolute joint to each of the revolute joints of hmm arms one after another. In designing the algorithms we focus on seeking closed-form solutions with high accuracy because we aim at applying them to human computer interaction for ubiquitous computing and virtual reality.