• Journal of Broadcast Engineering
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• v.14 no.1
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• pp.81-84
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• 2009

This paper explores the possibility of describing objects from the change in the shape according to the change in viewpoint. Specifically, we sample the shapes from various viewpoints of a 3-D model, and apply dimension reduction by locally linear embedding. A low dimensional distribution of points are constructed, and characteristics of the object are described from this distribution. Also, we propose two 3-D retrieval methods by applying the iterative closest point algorithm, and by applying Fourier transform and measuring similarity by modified Housdorff distance, and present experimental results. The proposed method shows that the change of shape according to the change in viewpoint can describe the characteristics of an object.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.797-803
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• 2014

In this paper, 3D face recognition system is designed by using polynomial based on RBFNNs. In case of 2D face recognition, the recognition performance reduced by the external environmental factors such as illumination and facial pose. In order to compensate for these shortcomings of 2D face recognition, 3D face recognition. In the preprocessing part, according to the change of each position angle the obtained 3D face image shapes are changed into front image shapes through pose compensation. the depth data of face image shape by using Multiple Point Signature is extracted. Overall face depth information is obtained by using two or more reference points. The direct use of the extracted data an high-dimensional data leads to the deterioration of learning speed as well as recognition performance. We exploit principle component analysis(PCA) algorithm to conduct the dimension reduction of high-dimensional data. Parameter optimization is carried out with the aid of PSO for effective training and recognition. The proposed pattern classifier is experimented with and evaluated by using dataset obtained in IC & CI Lab.

• Journal of Industrial Convergence
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• v.16 no.1
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• pp.35-40
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• 2018

The procedural generation algorithm is an algorithm that automatically generates a content to be used in a game by repeatedly executing a series of rules. As the size of the game increases, the amount of content used in the game increases. Accordingly, artificial intelligence research is actively conducted to automatically generate game contents using game artificial intelligence such as procedural generation. In this paper, we propose an algorithm to create 3D game world using procedural generation. The proposed algorithm generates a two-dimensional contour in which the path is naturally connected using Perlin-Noise whose noise is gradually changed. A three-dimensional Height-Map is created based on the generated two-dimensional contour lines. The generated Height-Map show that the shape of the map is normal and that the player is able to move around all the sections as in the game world created by hand. In the future, we will improve the performance of algorithms and apply them to game.

• Journal of Internet Computing and Services
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• v.18 no.3
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• pp.29-36
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• 2017

In these days, 3D dynamic simulation is closely related to many industries. In the past, physically-based 3D simulation was used mainly in the car crash or construction related fields, but it also plays an important role in movies or games today. Many mathematical computations are needed to represent the 3D object realistically, but it is difficult to process a large amount of calculations for simulation of application based on CPU in real-time. Recently, with the advanced graphic hardware and improved architecture, GPU can be utilized for the general purposes of computation function as well as graphic computation. Many approaches using GPU have been applied for various research fields. In this paper, we analyze the performance variation of two cloth simulation algorithms based on GPU according to the change of execution properties of GPU shaders in oder to optimize the performance of GPU-based cloth simulation. Cloth simulation is implemented by the spring centric algorithm and node centric algorithm with GPU parallel computing using compute shader of GLSL 4.3. We compare the performance of between these algorithms according to the change of the size and dimension of work group. The experiment is repeated to 10 times during 5,000 frames for each test and experimental results are provided by averaging of FPS. The experimental result shows that the node centric algorithm is executed in higher speed than the spring centric algorithm.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.273-279
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• 2014

In this paper, we propose a novel algorithm for three dimensional positioning system and implement a system over indoor wireless channel. A commercial modules are used for mobile and fixed nodes which are product of German company Nanotron Co. This module adopts chirp spread spreading scheme as modulation method to improve the ranging resolution and the module satisfies the IEEE standard 802.15.4a. The distance computation is based on received signal strength(RSS) levels and trilateration method. A testbed was set up to measure and compare the positioning estimation error of the proposed algorithm. The experiments results showed that the accuracy of location estimation was sufficiently good as much as 1m distance error in a wireless environment in an office building.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.425-430
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• 2015

This paper is a study to improve the classification efficiency of rotating objects by using deep neural networks to which a deep learning algorithm was applied. For the classification experiment of rotating objects, COIL-20 is used as data and total 3 types of classifiers are compared and analyzed. 3 types of classifiers used in the study include PCA classifier to derive a feature value while reducing the dimension of data by using Principal Component Analysis and classify by using euclidean distance, MLP classifier of the way of reducing the error energy by using error back-propagation algorithm and finally, deep learning applied DBN classifier of the way of increasing the probability of observing learning data through pre-training and reducing the error energy through fine-tuning. In order to identify the structure-specific error rate of the deep neural networks, the experiment is carried out while changing the number of hidden layers and number of hidden neurons. The classifier using DBN showed the lowest error rate. Its structure of deep neural networks with 2 hidden layers showed a high recognition rate by moving parameters to a location helpful for recognition.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.2
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• pp.13-20
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• 2014

In this paper, we implemented the object scanning with nxtOSEK which is an open source platform. nxtOSEK consists of device driver of leJOS NXJ C/Assembly source code, TOPPERS/ATK(Automotive real time Kernel) and TOPPERS/JSP Real-Time Operating System source code that includes ARM7 specific porting part, and glue code make them work together. nxtOSEK can provide ANSI C by using GCC tool chain and C API and apply for real-time multi tasking features. We experimented the 3D scanning with ultra sonic and laser sensor which are made directly by laser module diode and experimented the measurement of scanning the object by knowing x, y, and z coordinates for every points that it scans. In this paper, the laser module is the dimension of $6{\times}10[mm]$ requiring 5volts/5[mW], and used the laser light of wavelength in the 650[nm] range. For detecting the object, we used the beacon detection algorithm and as the laser light swept the objects, the photodiode monitored the ambient light at interval of 10[ms] which is called a real time. We communicated the 3D scanning platform via bluetooth protocol with host platform and the results are displayed via DPlot graphic tool. And therefore we enhanced the functionality of the 3D scanner for identifying the image scanning with laser sensor modules compared to ultra sonic sensor.

• Journal of Computing Science and Engineering
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• v.11 no.3
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• pp.79-91
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• 2017

In this paper, the abdominal-deformation measurement scheme is conducted on a shape-flexible mannequin using the DIC technique in a stereo-vision system. Firstly, during the integer-pixel displacement search, a novel fractal dimension based on an adaptive-ellipse subset area is developed to track an integer pixel between the reference and deformed images. Secondly, at the subpixel registration, a new mutual-learning adaptive particle swarm optimization (MLADPSO) algorithm is employed to locate the subpixel precisely. Dynamic adjustments of the particle flight velocities that are according to the deformation extent of each interest point are utilized for enhancing the accuracy of the subpixel registration. A test is performed on the abdominal-deformation measurement of the shape-flexible mannequin. The experiment results indicate that under the guarantee of its measurement accuracy without the cause of any loss, the time-consumption of the proposed scheme is significantly more efficient than that of the conventional method, particularly in the case of a large number of interest points.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.4 s.95
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• pp.373-379
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• 2005

Papers on improvement of electromagnetic field uniformity in a reverberation chamber with 1D Quadratic Residue Diffuser of Schroeder method has been published several times. In this paper, to obtain improved electromagnetic field characteristics and field uniformity in a reverberation chamber, cubical residue diffuser sets of Schroeder type are designed for a chamber in $2.3\;\cal{GHz}\~3\;\cal{GHz}$. The FDTD(Finite-Difference Time-Domain) technique is used to analyze the field characteristics in a chamber. Cubical residue algorithm and 2D arrangement show more randomness than the previous study results. The characteristics of tolerance, polarity, deviations, as well as power efficency, are improved with cubical residue diffuser sets in a chamber.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.1
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• pp.46-49
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• 2012

Gears are reliable and efficient power transmission elements. They have been widely used in all kinds of machinery. Nowadays, resource conservation energy conservation environmental improvements from the request of the compact, light weight, high efficiency, low cost Higher efficiency is required. Tooth root and bottom profiles of cylindrical gears affect bending fatigue life, but they are hard to measure with conventional gear measuring machine(GMM), because GMM is normally customized to measure only gear working flanks. The authors try to develop a new type of GMM by installing an extra 3D scanning probe and control software to measure tooth root and bottom profiles. First, in order to measure in various directions, a 3D scanning probe has been attached to the GMM developed. Next, calibration algorithm has been developed. Deviations of the calibration results are measured and it is found that systematic error must be caused by heat from driving motors. A new alternative GMM with driving motors generating less heat was designed and two GMMs are compared. Finally, 3 Dimension measurement of tooth root and bottom profiles of cylindrical gears is described.