• Journal of the Korea Computer Graphics Society
• /
• v.18 no.3
• /
• pp.1-7
• /
• 2012

In this paper, we propose a method to compute the interface between protein molecules. When a molecules is represented as a set of spheres with van der Waals radii, the distance from a spatial point p to the molecule corresponds to the distance from p to the closet sphere. The molecular interface is composed of equi-distant points from two molecules. Our algorithm decomposes the space into a set of voxels, and then constructs a voxel map by storing the information of spheres intersecting each voxel. By using the voxel map, we compute the distance between a point and the molecule. We also use GPU for the parallel processing, and efficiently approximate the interface of a pair of molecules.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.3
• /
• pp.1630-1638
• /
• 2015

The finite element analysis has become an essential process to investigate the structural performance in many industry fields. In addition, the computer's performance is improving rapidly, but in large design problems, there is a limit to apply the optimal design techniques. For this, it is general to introduce a metamodel based optimization technique. The method to generate an approximate model can be classified into curve fitting and interpolation, and each representative one is response surface model and kriging interpolation method. This study proposes an ensemble model made of RSM and kriging to solve a structural design problem. The suggested method is applied to the designs of two bar and automobile outer tie rod.

• Journal of the Korea Computer Graphics Society
• /
• v.25 no.5
• /
• pp.11-20
• /
• 2019

With the development of deep learning technology, research is being actively carried out on user-friendly interfaces that are suitable for use in virtual reality or augmented reality applications. To support the interface using the user's hands, this paper proposes a deep learning-based fingertip detection method to enable the tracking of fingertip coordinates to select virtual objects, or to write or draw in the air. After cutting the approximate part of the corresponding fingertip object from the input image with the Grad-CAM, and perform the convolution neural network with Atrous Convolution for the cut image to detect fingertip location. This method is simpler and easier to implement than existing object detection algorithms without requiring a pre-processing for annotating objects. To verify this method we implemented an air writing application and showed that the recognition rate of 81% and the speed of 76 ms were able to write smoothly without delay in the air, making it possible to utilize the application in real time.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.44 no.5
• /
• pp.58-65
• /
• 2007

As multimedia portable devices become popular, the amount of computation for processing data including video compression has significantly increased. Various researches for low power consumption of the mobile devices and real time processing have been reported. Motion Estimation is responsible for 67% of H.264 encoder complexity. In this research, a new circuit is designed for motion estimation. The new circuit uses motion prediction based on approximate SAD, Alternative Row Scan (ARS), DAU, and FDVS algorithms. Our new method can reduce the amount of computation by 75% when compared to multi-frame motion estimation suggested in JM8.2. Furthermore, optimal number and size of reference frame blocks are determined to reduce computation without affecting the PSNR. The proposed Motion Estimation method has been verified by using the hardware and software Co-Simulation with iPROVE. It can process 30 CIF frames/sec at 50MHz.

• Journal of the Korea Computer Graphics Society
• /
• v.20 no.1
• /
• pp.13-19
• /
• 2014

In this paper, we introduce a real-time method to render a 3D scene using image-based lighting. Previous approaches for image-based lighting focused on diffuse reflection and mirror-like specular reflection. In this paper, we provide a simple preprocessing approach to efficiently approximate Phong reflection model, which has been used for computer graphics applications for several decades. For diffuse reflection, we generate a texture map for diffuse reflection by integrating the source image in preprocessing step, similarly to the previous approaches. We adopt the similar idea to produce a set of specular reflection maps for various material shininess. By doing this, we can render a dynamic scene without high computational complexity or numerous texture map access.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.10a
• /
• pp.532-538
• /
• 1998

In this paper, a new adaptive fuzzy inference method using neural network based fuzzy reasoning is proposed to make a fuzzy logic control system more adaptive and more effective. In most cases, the design of a fuzzy inference system rely on the method in which an expert or a skilled human operator would operate in that special domain. However, if he has not expert knowledge for any nonlinear environment, it is difficult to control in order to optimize. Thus, using the proposed adaptive structure for the fuzzy reasoning system can controled more adaptive and more effective in nonlinear environment for changing input membership functions and output membership functions. The proposed fuzzy inference algorithm is called adaptive neuro-fuzzy control(ANFC). ANFC can adapt a proper membership function for nonlinear plant, based upon a minimum number of rules and an initial approximate membership function. Nonlinear function approximation and rotary inverted pendulum control system ar employed to demonstrate the viability of the proposed ANFC.

• Transactions on Control, Automation and Systems Engineering
• /
• v.2 no.3
• /
• pp.189-195
• /
• 2000

The mathematical solutions of the stability convergence are important problems in system control. In this paper such problems are analyzed and resolved for system control using multilayer neural networks. We describe an algorithm to control an unknown nonlinear system with a disturbance, using a multilayer neural network. We include a disturbance among the modeling error, and the weight update rules of multilayer neural network are derived to satisfy Lyapunov stability. The overall control system is based upon the feedback linearization method. The weights of the neural network used to approximate a nonlinear function are updated by rules derived in this paper . The proposed control algorithm is verified through computer simulation. That is as the weights of neural network are updated at every sampling time, we show that the output error become finite within a relatively short time.

• Journal of information and communication convergence engineering
• /
• v.16 no.1
• /
• pp.38-42
• /
• 2018

In this paper, we consider measurement allocation problem in a spatially correlated sensor field. Our goal is to determine the probability of each sensor's being measured based on its contribution to the estimation reliability; it is desirable that a sensor improving the estimation reliability is measured more frequently. We consider a spatial correlation model of a sensor field reflecting transmission power limit, noise in measurement and transmission channel, and channel attenuation. Then the estimation reliability is defined distortion error between event source and its estimation at sink. Motivated by the correlation nature, we model the measurement allocation problem into a cooperative game, and then quantify each sensor's contribution using Shapley value. Against the intractability in the computation of exact Shapley value, we deploy a randomized method that enables to compute the approximate Shapley value within a reasonable time. Besides, we envisage a measurement scheduling achieving the balance between network lifetime and estimation reliability.

• Journal of Korea Multimedia Society
• /
• v.22 no.10
• /
• pp.1142-1148
• /
• 2019

Reconstruction of the three-dimensional (3D) environment is a key aspect of augmented reality and augmented virtuality, which utilize and incorporate a user's surroundings. Such reconstruction can be easily realized by employing a Kinect device. However, multiple Kinect devices are required for enhancing the reconstruction density and for spatial expansion. While employing multiple Kinect devices, they must be calibrated with respect to each other in advance, and a marker is often used for this purpose. However, a marker needs to be placed at each calibration, and the result of marker detection significantly affects the calibration accuracy. Therefore, a user-friendly, efficient, accurate, and marker-less method for calibrating multiple Kinect devices is proposed in this study. The proposed method includes a joint tracking algorithm for approximate calibration, and the obtained result is further refined by applying the iterative closest point algorithm. Experimental results indicate that the proposed method is a convenient alternative to conventional marker-based methods for calibrating multiple Kinect devices. Hence, the proposed method can be incorporated in various applications of augmented reality and augmented virtuality that require 3D environment reconstruction by employing multiple Kinect devices.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.5
• /
• pp.137-151
• /
• 2014

This paper proposes a method of detecting object of interest(OOI) in general natural images. OOI is subjectively estimated by human in images. The vision of human, in general, might focus on OOI. As the first step for automatic detection of OOI, candidate regions of OOI are detected by using a saliency map based on the human visual perception. A saliency map locates an approximate OOI, but there is a problem that they are not accurately segmented. In order to address this problem, in the second step, an exact object region is automatically detected by combining graph-based image segmentation and skeletonization. In this paper, we calculate the precision, recall and accuracy to compare the performance of the proposed method to existing methods. In experimental results, the proposed method has achieved better performance than existing methods by reducing the problems such as under detection and over detection.