• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.692-703
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• 2021

Recently, with the development of computer graphics technology, research on technology for expressing real objects as more realistic virtual graphics is being actively conducted. Point cloud is a technology that uses numerous points, including 2D spatial coordinates and color information, to represent 3D objects, and they require huge data storage and high-performance computing devices to provide various services. Video-based Point Cloud Compression (V-PCC) technology is currently being studied by the international standard organization MPEG, which is a projection based method that projects point cloud into 2D plane, and then compresses them using 2D video codecs. V-PCC technology compresses point cloud objects using 2D images such as Occupancy map, Geometry image, Attribute image, and other auxiliary information that includes the relationship between 2D plane and 3D space. When increasing the density of point cloud or expanding an object, 3D calculation is generally used, but there are limitations in that the calculation method is complicated, requires a lot of time, and it is difficult to determine the correct location of a new point. This paper proposes a method to generate additional points at more accurate locations with less computation by applying 2D interpolation to the image on which the point cloud is projected, in the V-PCC technology.

• Journal of KIISE
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• v.43 no.5
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• pp.516-523
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• 2016

For old-age makeups, makeup artists first make a mold cast of an actor's face using plaster and then sculpt wrinkles in clay on the plaster mold. After finishing the clay sculpture, its negative plaster mold is fabricated and silicone skin patches are finally made for application to the actor's face. This process takes a few days and is tedious for actors and makeup artists. With recent advances in 3D printing and scanning technology, it is becoming easier to scan and fabricate 3D faces. This paper presents a new pipeline composed of facial scanning, interactive wrinkle modeling, and mold printing stages to easily and efficiently fabricate silicone masks for old-age makeups without the use of plaster and clay. An intuitive sketch interface based on a normal map is proposed for the creation of wrinkles in real time, even with a high-resolution face model. Then the geometry of the final wrinkles is reconstructed using a depth map and the negative mold of the wrinkled face is printed. We also show that the presented pipeline can fabricate a silicone mask more conveniently than the traditional one that consists of pouring silicone into the prepared negative mold and then overlapping the mold with the original positive one.

• Journal of the Korea Computer Graphics Society
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• v.23 no.1
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• pp.25-32
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• 2017

This paper proposes a novel acceleration method for particle based large scale fluid simulation. Traditional particle-based fluid simulation has been implemented by interacting with physical quantities of neighbor particles through the Smoothed Particle Hydrodynamics(SPH) technique[1]. SPH method has the characteristic that there is no visible change compared to the computation amount in a part where the particle movement is small, such as a calm surface or inter-fluid. This becomes more prominent as the number of particles increases. Previous work has attempted to reduce the amount of spare computation by adaptively dividing each part of the fluid. In this paper, we propose a technique to calculate the motion of the entire particles by using the physical quantities of the near sampled particles by sampling the particles inside the fluid at regular intervals and using them as reference points of the fluid motion. We propose a technique to adaptively generate a triangle map based on the position of the sampled particles in order to efficiently search for nearby particles, and we have been able to interpolate the physical quantities of particles using the barycentric coordinate system. The proposed acceleration technique does not perform any additional correction for two classes of fluid particles. Our technique shows a large improvement in speed as the number of particles increases. The proposed technique also does not interfere with the fine movement of the fluid surface particles.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.437-446
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• 2012

A face detection algorithms using two-dimensional (2-D) intensity or color images have been studied for decades. Recently, with the development of low-cost range sensor, three-dimensional (3-D) information (i.e., depth image that represents the distance between a camera and objects) can be easily used to reliably extract facial features. Most people have a similar pattern of 3-D facial structure. This paper proposes a face detection method using intensity and depth images. At first, adaboost algorithm using intensity image classifies face and nonface candidate regions. Each candidate region is divided into $5{\times}5$ blocks and depth values are averaged in each block. Then, $5{\times}5$ block rank pattern is constructed by sorting block averages of depth values. Finally, candidate regions are classified as face and nonface regions by matching the constructed depth map based block rank patterns and a template pattern that is generated from training data set. For template matching, the $5{\times}5$ template block rank pattern is prior constructed by averaging block ranks using training data set. The proposed algorithm is tested on real images obtained by Kinect range sensor. Experimental results show that the proposed algorithm effectively eliminates most false positives with true positives well preserved.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.321-328
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• 2014

In this paper, we present a MapReduce-based mobility pattern mining system which can predict efficiently the next place of mobile users. It learns the mobility pattern model of each user, represented by Hidden Markov Models(HMM), from a large-scale trajectory dataset, and then predicts the next place for the user to visit by applying the learned models to the current trajectory. Our system consists of two parts: the back-end part, in which the mobility pattern models are learned for individual users, and the front-end part, where the next place for a certain user to visit is predicted based on the mobility pattern models. While the back-end part comprises of three distinct MapReduce modules for POI extraction, trajectory transformation, and mobility pattern model learning, the front-end part has two different modules for candidate route generation and next place prediction. Map and reduce functions of each module in our system were designed to utilize the underlying Hadoop infrastructure enough to maximize the parallel processing. We performed experiments to evaluate the performance of the proposed system by using a large-scale open benchmark dataset, GeoLife, and then could make sure of high performance of our system as results of the experiments.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.21-29
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• 2011

At existing skin detection methods using skin color information defined based on the prior knowldege, threshold value to be used at the stage of dividing the backround and the skin region was decided on a subjective point of view through experiments. Also, threshold value was selected in a passive manner according to their background and illumination environments in these existing methods. These existing methods displayed a drawback in that their performance was fully influenced by the threshold value estimated through repetitive experiments. To overcome the drawback of existing methods, this paper propose a skin region detection method using a histogram approximation based on the mean shift algorithm. The proposed method is to divide the background region and the skin region by using the mean shift method at the histogram of the skin-map of the input image generated by the comparison of the similarity with the standard skin color at the CbCr color space and actively finding the maximum value converged by brightness level. Since the histogram has a form of discontinuous function accumulated according to the brightness value of the pixel, it gets approximated as a Gaussian Mixture Model (GMM) using the Bezier Curve method. Thus, the proposed method detects the skin region by using the mean shift method and actively finding the maximum value which eventually becomes the dividing point, not by using the manually selected threshold value unlike other existing methods. This method detects the skin region high performance effectively through experiments.

• Journal of Digital Contents Society
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• v.10 no.4
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• pp.493-499
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• 2009

Three methods frequently used for Hangul display in computer systems are Standard Johab Code in which each of Hangul consonants and vowels is given a 5-bit code and each syllable created by combining them forms a 2-byte code, Standard Wansung Code in which each of all the syllables generally used for Hangul presentation forms a 2-byte code, and Unicode in which each syllable in most of the world's language systems is given a unique code so that it allows computers to consistently represent and manipulate them in a unified manner. An embedded system in general has a lower processing power and a limited amount of storage space, compared to a personal compute(PC) system. According to its usage, however, the former may have a processing power equal to that of the latter. Hence, when Hangul display needs to be adopted, an embedded system must choose a display method suitable for its own resource environment. This paper introduces a TFT LCD initialization method and pixel display functions of an LN2440SBC embedded board on which an LP35, a 3.5" TFT LCD kit, is attached. Using the initialization and pixel display functions, in addition, we compare three aforementioned Hangul display methods, in terms of their processing speeds and amounts of memory space required. According to experiments, Standard Johab Code requires less amount of memory space but more processing time than Standard Wansung Code, and Unicode requires the largest amount of memory space but the least processing time.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.13-24
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• 2008

The multi robot operation technique has emerged as one of the most important research subjects that focus on minimizing redundancy in space exploration and maximizing the efficiency of operation. For an efficient operation of the multi robot systems, the movement of each Single robot in the multi robot systems should be properly observed and controlled. This paper suggests Multi Robot Management System to minimize redundancy in space exploration by assigning exploration space to each robot efficiently to take advantage of the RFID. Also, this paper has suggested fault tolerance technique that detects disable Single robot and substitute it by activated Single robot in order to ensure overall exploration and improve efficiency of exploration. Proposed system overcomes previous fault that it is difficult for central server to detect exact position of robot by using RFID system and Home Robot. Designated Home robot manages each Single robot efficiently and assigns the best suited space to Single robot by using RFID Tag Information. Proposed multi robot management system uses RFID for space assignment, Localization and Mapping efficiently and not only maximizes the efficiency of operation, but also ensures reliability by supporting fault-tolerance, compared with Single robot system. Also, through simulation, this paper proves efficiency of spending time and redundancy rates between multi robot management applied by proposed system and not applied by proposed system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.1
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• pp.58-63
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• 2020

This paper proposes the method for improving the localization accuracy of the mobile robot based on the stereo camera. To restore the position information from stereo images obtained by the stereo camera, the corresponding point which corresponds to one pixel on the left image should be found on the right image. For this, there is the general method to search for corresponding point by calculating the similarity of pixel with pixels on the epipolar line. However, there are some disadvantages because all pixels on the epipolar line should be calculated and the similarity is calculated by only pixel value like RGB color space. To make up for this weak point, this paper implements the method to search for the corresponding point simply by calculating the gap of x-coordinate when the feature points, which are extracted by feature extraction and matched by feature matching method, are a pair and located on the same y-coordinate on the left/right image. In addition, the proposed method tries to preserve the number of feature points as much as possible by finding the corresponding points through the conventional algorithm in case of unmatched features. Because the number of the feature points has effect on the accuracy of the localization. The position of the mobile robot is compensated based on 3-D coordinates of the features which are restored by the feature points and corresponding points. As experimental results, by the proposed method, the number of the feature points are increased for compensating the position and the position of the mobile robot can be compensated more than only feature extraction.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.646-654
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• 2007

In recent years, the use of text inserted into TV contents has grown to provide viewers with better visual understanding. In this paper, video text is defined as superimposed text region located of the bottom of video. Video text extraction is the first step for video information retrieval and video indexing. Most of video text detection and extraction methods in the previous work are based on text color, contrast between text and background, edge, character filter, and so on. However, the video text extraction has big problems due to low resolution of video and complex background. To solve these problems, we propose a method to extract text from videos using the Harris corner detector. The proposed algorithm consists of four steps: corer map generation using the Harris corner detector, extraction of text candidates considering density of comers, text region determination using labeling, and post-processing. The proposed algorithm is language independent and can be applied to texts with various colors. Text region update between frames is also exploited to reduce the processing time. Experiments are performed on diverse videos to confirm the efficiency of the proposed method.