• Journal of Industrial Technology
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• v.19
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• pp.173-178
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• 1999

In many areas of technology there are machines and systems controllable in up to six degrees of freedom. Helicopters and underwater vehicles, industrial robots are among the first representatives of this category. They need six degrees of freedom in order to move and orient within their workspace. An even broader and more explosively growing area is 3D computer graphics and virtual environment. In this work, functions of 3D input device are described and two types of commercial 3D input device are presented. Then, a preliminary experiment of a low cost 6 axis force/moment sensor is presented that can also be sued as a 3D input device. A low cost force/moment sensor and its application in robot teaching experiment is described. It computes the direction of 3 components of the force and 3 components of the moment applied by human holding the sensor by hand. The concept is shown by an experiment where the tool position and orientation of a robot in 3 dimensional space is controlled by the proposed sensor.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.535-540
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• 2000

This paper presents the development of a Parallel-Typed CNC Machining Tool. It is specially designed to machine a complex shaped workpiece by controlling the orientation of the tool. The inverse/direct kinematics of a parallel mechanism is derived and implemented in a PC based controller. With graphics icons, the GUI (Graphic User Interface) program is developed for the CNC programing. The calibration is accomplished by geometric constraint motion, which is a parallel motion of the platform with respect to a table. The calibration result is introduced and the future study is proposed.

• The Journal of Korea Robotics Society
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• v.10 no.4
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• pp.230-244
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• 2015

Continuous-path motion control such as resolved motion rate control requires online solving of the inverse differential kinematics for a robot. However, the solution space of the inverse differential kinematics related to Jacobian J is not well-established. In this paper, the solution space of inverse differential kinematics is analyzed through categorization of mapping conditions between joint velocities and end-effector velocity of a robot. If end-effector velocity is within the column space of J, the solution or the minimum norm solution is obtained. If it is not within the column space of J, an approximate solution by least-squares is obtained. Moreover, this paper introduces an improved mapping diagram showing orthogonality and mapping clearly between subspaces, and concrete examples numerically showing the concept of several subspaces. Finally, a solver and graphics user interface (GUI) for inverse differential kinematics are developed using MATLAB, and the solution of inverse differential kinematics using the GUI is demonstrated for a vertically articulated robot.

• Korean Journal of Applied Biomechanics
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• v.14 no.1
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• pp.99-115
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• 2004

In order to Know the correct swing methods in golf swing it is important to understand the whole swing path but also the concept of swing plane. But, most amateur golfers don't Know the concept of swing plane well. Therefore this study was trying to make a good material that makes the concept of swing plane easy to understand. A good swing motion data was obtained from a professional golfer using the three-dimensional DLT method. This swing motion was divided into 10 phases and evaluated using the concept of swing plane. The result of the analyze show a good matches between the path of the club and swing plane. This result was summarized as a 3 dimensional graphics to provide a good material to teach the golf swing well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2444-2463
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• 2020

Significant detection of video can more rationally allocate computing resources and reduce the amount of computation to improve accuracy. Deep learning can extract the edge features of the image, providing technical support for video saliency. This paper proposes a new detection method. We combine the Convolutional Neural Network (CNN) and the Deep Bidirectional LSTM Network (DB-LSTM) to learn the spatio-temporal features by exploring the object motion information and object motion information to generate video. A continuous frame of significant images. We also analyzed the sample database and found that human attention and significant conversion are time-dependent, so we also considered the significance detection of video cross-frame. Finally, experiments show that our method is superior to other advanced methods.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.1-11
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• 2009

Recently there has arisen concern in both the database community and the graphics society about data retrieval from large motion databases because the high dimensionality of motion data implies high costs. In this circumstance, finding an effective distance measure and an efficient query processing method for such data is a challenging problem. This paper presents an elaborate motion query processing system, SMoFinder (Similar Motion Finder), which incorporates a novel kinematic distance measure and an efficient indexing strategy via adaptive frame segmentation. To this end, we regard human motions as multi-linkage kinematics and propose the weighted Minkowski distance metric. For efficient indexing, we devise a new adaptive segmentation method that chooses representative frames among similar frames and stores chosen frames instead of all frames. For efficient search, we propose a new search method that processes k-nearest neighbors queries over only representative frames. Our experimental results show that the size of motion databases is reduced greatly (${\times}1/25$) but the search capability of SMoFinder is equal to or superior to that of other systems.

• Journal of the Korea Computer Graphics Society
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• v.8 no.3
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• pp.17-23
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• 2002

Motion capture system is widely used nowadays in the entertainment industry like movies, computer games and broadcasting. This system consist of several high resolution and high speed CCD cameras and expensive frame grabbing hardware for image acquisition. KAIST VR laboratory focused on low cost system for a few years and have been developed a LAN based optical motion capture system. But, by using low cost system some problems like occlusion, noise and swapping of markers' trajectory can be occurred. And more labor intensive work is needed for post-processing process. In this thesis, we propose a trajectory rectification algorithm by confidence model of markers attached on actor. Confidence model is based on graph structure and consist of linkage, marker and frame confidence. To reduce the manual work in post-processing, we have to reconstruct the marker graph by maximizing the frame confidence.

• Journal of the Korea Computer Graphics Society
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• v.6 no.3
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• pp.9-15
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• 2000

We Propose a sensor fusion technique for motion capture system. In our system, two kinds of sensors are used for mutual assistance. Four magnetic sensors(markers) are attached on the upper arms and the back of the hands for assisting twelve optical sensors which are attached on the arms of a performer. The optical sensor information is not always complete because the optical markers can be hidden due to obstacles. In this case, magnetic sensor information is used to link discontinuous optical sensor information. We use a system identification techniques for modeling the relation between the sensors' signals. Dynamic systems are constructed from input-output data. We determine the best model from the set of candidate models using the canonical system identification techniques. Our approach is using a simple signal processing technique currently. In the future work, we will propose a new method using other signal processing techniques such as Wiener or Kalman filter.

• Journal of the Korea Computer Graphics Society
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• v.23 no.1
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• pp.39-48
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• 2017

We present penetration depth (PD) computation algorithms using explicit Minkowski sum construction ($PD_e$) and implicit Minkowski sum construction ($PD_i$). Minkowski sum construction is the most time consuming part in fast PD computation. In order to address this issue, we find a candidate solution using a centroid difference and motion coherence. Then, $PD_e$ constructs or updates partial Minkowski sum around the candidate solution. In contrast, $PD_i$ constructs only a tangent plane to the Minkowski sums iteratively. In practice, our algorithms can compute PD for complicated models consisting of thousands of triangles in a few milli-seconds. We also discuss the benefits of using different construction of Minkowski sums in the context of PD.

• Journal of the Korea Computer Graphics Society
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• v.18 no.3
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• pp.9-16
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• 2012

In this paper, we present a new method for reconstructing detailed facial expression from roughly captured data with a small number of markers. Because of the difference in the required capture resolution between the full-body capture and the facial expression capture, they hardly have been performed simultaneously. However, for generating natural animation, a simultaneous capture for body and face is essential. For this purpose, we provide a method for capturing the detailed facial expression only with a small number of markers. Our basic idea is to build a database for the facial expressions and apply the principal component analysis for reducing the dimensionality. The dimensionality reduction enables us to estimate the full data from a part of the data. We justify our method by applying it to dynamic scenes to show the viability of the method.