Earticle

사용자의 수요가 증가함으로 인하여 최근의 마커 기반 증강현실 기술은 제스처 기반 인간-컴 퓨터 상호작용 분야에서 주목을 받고 있다. 그러나 개체가 프레임에서 빠른 움직임을 보일 때 발 생하는 모션 블러 효과에 의하여 마커의 추적 및 감지의 한계점이 발생한다. 기존의 디블러링 기 술들에서 전체 프레임 중 특정 프레임을 추출하는 작업이 없다면 실시간 비디오에서 사용하기에 문제가 있다. 본 논문에서는 인간-컴퓨터 상호작용을 위하여 ArUco 마커를 사용한 특징점 기반 광학흐름 추적 방법을 제안하며, 마커를 이용한 자세 추정 방법을 설명한다. 이 방법은 ArUco 마 커를 감지하고 특수한 마커 추적 방법을 통해 마커 감지를 보완한다. 특히 마커 추적 방법은 FAST 알고리즘을 사용하여 특징점을 추출하고 루카스-카나데 방법을 사용하여 특징점의 움직임 을 분석하여 움직임 벡터를 계산한다. 또한 Perspective-n-Point 문제를 해결하여 마커 포즈 추정 을 구현했다. 제안된 시스템은 기존의 방법보다 높은 검출률을 보였으며, 마커를 포함한 비디오 에서 프레임 처리 속도가 약 37% 향상되었다. 또한 마커 포즈 추정을 그래픽으로 구현하였다. 이 연구는 실제 환경에서 카메라를 통한 제스처 기반 인간-컴퓨터 상호작용 분야와 또한 이동 로봇 분야에도 도움이 될 것이라 기대된다.

Recently, marker-based augmented reality technology has attracted attention in gesture based human-computer interaction due to the users' demand. However, the blur effect that occurs when the object shows fast motion in frames limits the marker detection and tracking. Conventional de-blurring techniques are not effective for real-time video without the task of extracting a specific frame from a full frame. In this paper, we proposed the algorithm which detects special marker first, and also tracks point features of markers based on optical flow method. Especially, marker tracking method extracts point features also using the FAST algorithm and calculates motion vectors by analyzing the motion of point features using Lucas-Kanade method. Also, we implemented a marker pose estimation by solving Perspective-n-Point problem. Our proposed system showed more improved results than conventional methods especially with the rate of 37% higher in the frame processing speed of marker tracking video. In addition, the marker pose estimation was graphically represented. It is expected that this research will be useful for gesture-based human-computer interaction field and mobile robot field through camera in real environment.

최근 컴퓨터 교육에서 프로그래밍에 대한 관심이 높아지고 있다. 학습에서 논리력과 창의력의 요구가 늘어나고 있는 추세에 힘입어 컴퓨터 교육 분야에서도 프로그래밍 학습을 통한 논리력과 창의력을 함양하려는 다양한 시도가 이루어지고 있다. 프로그램은 알고리즘을 컴퓨터 언어로 구현한 것이므로 문제해결의 핵심은 논리적 해결 방법의 고안 즉, 알고리즘의 고안에 있다. 알고리즘의 중요성을 인식한다면 이제 알고리즘 교육에 대한 방향 정립을 위한 체계적 연구가 필요한 시점에 와 있다고 볼 수 있다. 지금까지 주로 정렬, 탐색과 같은 특정 문제를 중심으로 한 문제 종속적이고 개별적인 알고리즘 학습을 강조해 왔다. 본 논문에서는 문제 독립적, 집단적 성질을 고려하는 문제 해결의 개념적 유형이라는 관점에서 개념적 알고리즘(conceptual algorithm)을 정의한다. 개념적 알고리즘의 유형적 특성을 바탕으로 개별적, 문제 종속적인 기존의 알고리즘 교육과 구분되는 체계적, 문제 독립적, 알고리즘적인 문제 해결력을 지향하는 알고리즘 교육의 새로운 방향을 제안한다.

Computer programming in computer education draws much attention recently. Encouraged by the increased tendency of acquiring logical ability and creativity through learning, various attempts have been made to develop them through learning computer programming in the area of computer education as well. The fact that a computer program is the representation of a computer algorithm expressed in a computer language makes us realize that the devise of a logical method for a solution - i.e., the design of an algorithm - is the key to the solution of a problem. Recognizing the importance of computer algorithm would lead us to such a point that systematic investigations for directional establishment for algorithm education are necessary. We observe that researches on teaching computer algorithm have concentrated mostly on specific problems such as sorting and searching, which can be characterized as problem-dependent and individual. In this paper, the idea of conceptual algorithm is stated from the standpoint of conceptual types of problem-solving methods which are considered as problem-independent and collective. A novice approach to algorithm education based on the characteristics of types of conceptual algorithms is proposed for the purpose of developing systematic, problem-independent, algorithmic problem-solving capabilities of learners, which is widely different from the current methods of individual and problem-dependent algorithm education.

본 연구는 콰욜라 작품에서 컴퓨터 알고리즘 기술이 주체로서, 인간이 재현한 이미지를디지털 이미지로 재창조하는 데서 발생한 숭고적 의미와 특성을 고찰한다. 그리고 이를 통해콰욜라 작품이 인간중심성을 비판적으로 성찰한다는 점을 살펴본다. 숭고에서 주체는 변형되고 비결정화되어 이전과 다른 창조적 자아로 거듭난다. 숭고에서 주체의 이런 양상은 주체로서 알고리즘 기술이 대상에 야기하는 현상과 유사하다. 알고리즘 기술은 대상을 데이터화함으로써 대상에 창조적 잠재력을 준다. 데이터로서 비결정화 된 대상은 다른 존재들로 다시변형되어 이전과 불일치할 가능성을 갖기 때문이다. ≪포로들 #B06 Captives #B06≫ (2014)과 ≪유적: 프로방스 Remains: Provance≫(2016)에서 알고리즘 기술은 대상을 변형, 비결정화 하고 이전과 불일치하게 만들어 대상에 창조적 잠재력과 숭고적 특성을 준다. 그래서 인간 시각에 대한 차이를 발생시켜 인간 시각과 근본적으로 같지만 다른 형태를 지니는 기계의 시각을 제시한다. 그리하여 알고리즘 기술은 인간이 기계의 시각을 통해 자신에대한 메타적 보기를 가능케 한다.

This study explores the meaning and characteristics of the sublimeness brought forth by computer algorithm technology while it transforms human-created images into digital images. In the process, this paper will examine Davide Quayola’s works and show that they are indeed an attempt to critically reflect on anthropocentrism. In the sublime theory, the subject is metamorphosed into an indeterminate entity, and thus creatively reborn. This parallels the phenomenon that algorithm technology, as subject, induces to objects. Algorithm technology affords creative potential to objects by turning them into digital data. In Captive #B06 and Remains: Provence, algorithm technology metamorphoses objects and makes them indeterminate and disagreeing with their previous status, giving them creative potential and the characteristics of the sublimeness. The mechanical view that algorithm technology creates is fundamentally the same as the human view, but has a different form. Therefore, algorithm technology enables humans to meta-view themselves through the mechanical views.

For several years, keyboard and mouse have been used as the main interacting devices between users and computer games, but they are becoming outdated. Gesture-based human- computer interaction systems are becoming more popular owing to the emergence of virtual reality and augmented reality technologies. Therefore research on these systems has attracted a significant attention. The researches focus on designing the interactive interfaces between users and computers. Human-computer interaction is an important factor in computer games because it affects not only the experience of the users, but also the design of the entire game. In this research, we develop an particle filter-based face tracking method using color distributions as features, for the purpose of applying to gesture-based human-computer interaction systems for computer games. The experimental results proved the efficiency of particle filter and color features in face tracking, showing its potential in designing human-computer interactive games.

미래의 창의적인 문제해결력을 지닌 인재 양성을 위해, 본 연구는 초등학생들에게 지도하기 어렵고 학생들이 이해하기 힘든 컴퓨터과학원리 중 라우팅알고리즘에 대한 교수․학습방법을 설계해 이를 지도해 보고 이러한 학습내용이 초등학교 학생들이 이해할 수 있는지를 알아보고자 하는데 그 목적이 있다. 사전․사후 동형 검사지를 통해 지적인 영역을 평가하고, 수업 후의 소감문을 통해 정의적인 영역을 평가하였다. 그 결과 네트워크 중 라우팅알고리즘이 초등학생에게 가르쳐질 수 있음을 확인하고 초등학교 컴퓨터교육의 학습요소로서의 가능성을 제시한다.

The purpose of this study is to design and practice teaching and learning method for routing algorithm among computer science principle which is difficult to be taught to elementary school students and understood by students. And we find out whether elementary school students can understand those learning contents. Intellectual area was assessed through equivalent test paper before and after the test and emotional area was assessed through students' impressions after class. The test showed that routing algorithm could be taught to children. Therefore, this study presents the learnability of routing algorithm as a learning element of elementary school computer education.

초등학교 컴퓨터교육은 컴퓨터 사용기능을 익히는 것도 중요하지만 컴퓨터는 어떤 방법을 이용하여 계산을 하는지에 대한 원리를 이해하고 이를 통해 다른 문제를 해결해 낼 수 있는 능력을 키우는 것도 중요하다고 할 수 있다. 본 연구는 초등학생을 대상으로 자료구조의 검색과 정렬 알고리즘 학습내용을 재구성해 교수․학습 방법을 설계해 이를 지도해 보고 이러한 학습내용이 초등학교 학생들은 이해할 수 있는지를 알아보고자 하는데 연구의 목적이 있다. 사전․사후 동형 검사지를 통해 지적인 영역을 평가하고, 수업 후의 소감문을 통해 정의적인 영역을 평가하였다. 그 결과 자료구조 중 검색과 정렬 알고리즘이 초등학생에게 가르쳐 질 수 있음을 확인하고 초등학교 컴퓨터교육의 학습요소로서의 가능성을 제시한다.

Computer education is important to learn functions of computers, and it is necessary to enhance the ability such as high-power intelligence ability, originality, and positive thoughts on the future. In other words, not only is it important to learn functions to calculate using computers but also it is important to understand the principle of the way computers calculate and enlarge other abilities to solve other problems through understanding of the principle. Accordingly, this study aims to teach search and sort of data structure to a primary-school children. In addition its purpose is to design teaching and learning methods and teach according to the methods and find out whether primary-school children can understand the contents. Intelligent field was assessed through equivalent test before and after the test and emotional field through students' impressions after a lesson. The test showed that search and sort algorithm of data structure could be taught to children. That is, it presented the learnability of search and sort of data structure as a learning element of elementary school computer education.

AM-heap is a heap data structure with O(1) amortized insertion time and O(logn) deletion time complexities. This paper presents cache-aligned 4-ary AM-heap in which every node has four children except that the root has three children. In this heap, the leftmost node of each sibling has an index of a multiple of four. Also, every node index matches its corresponding array index and every sibling nodes smoothly fits into a single cache block. Our experimental results show that cache-aligned 4-ary AM-heap is faster than AM-heap as well as post-order heap.

The specific objective of this paper is to develop a computer vision algorithm to detect and count tangerine flowers in an image for estimate tangerine crops. The algorithm consists of image acquisition, Gaussian filter to remove noise, white color detection, counting of tangerine flowers. A Gaussian filter was used to reduce noise and illumination adjustment as much as possible for better clarity. It is observed that the developed method gives better valid output for tangerine flower detection in natural outdoor lighting, with different lighting condition without any alternative lighting source to control the luminance. The simulation result reveals that the method is reliable, feasible and efficient compared to other existing methods.

As a carrier of artificial intelligence research, computer game can establish a sound theoretical foundation for the research of non-zero-sum card games with imperfect information. In this paper, we first propose a game model based on the finite Moore automaton, which illustrates the implementation of the model for Niujiu card. At the same time, a novel search strategy combining IMP-minimax and Monte Carlo algorithm is presented in this model. Through the given algorithm, this paper accomplishes the simulation, including not only the process of minimal and optimal occupancy for the first player, but the available frequency of special card type. Experiments show that our model and algorithm are feasible and effective.

In computer aided diagnosis (CAD) process, one of the most challenging problems is data sparsity, which leads to the diagnosis results are not reliable. This paper proposes a clustering collaborative filtering based algorithm to solve the problem of data sparsity. In this paper, we use k-means clustering algorithm to cluster the same type of patients, and then adopt collaborative filtering method to fill the missing data values for each cluster, in this way to reduce the complexity of similarity calculation of collaborative filtering. The proposed method makes full use of the information-sharing mechanism of "similar patient population" to predict and fill the missing values. A hepatitis dataset is used for evaluating the performance of the algorithm. Results indicate that the proposed algorithm has better performance for medical record data sparsity problem.

In this paper, in order to assess the risk of network, network security assessment process being involved in the content in detail. The above-mentioned research-based support system platform security test and evaluate research of the safety situation assessment. Prediction subsystem detailed design and carry out the implementation. In this paper, network security issues, as a detailed study of neural networks knowledge. Focus on the evaluation methods and calculation rules of nerve network technology, it has been studied by specific examples. Calculation demonstrated the feasibility of neural network evaluation model through actual case, which pointed out the traditional methods. This paper focuses on the network security assessment based on neural network technology, extensive analysis of the proposed major modeling tool indicator system for network security analysis. The application of neural networks was a network security assessment and to optimize the network by genetic algorithm. The key parameter combination operated efficiency of neural networks to get better play.

The scarcity of automatic fire detection systems continues to be a problem that needs a serious attention in order to save human lives by preventing injuries and/or deaths. The newest innovations are continuing to use cameras and computer algorithms to analyze the visible effects of fire and its motion in their applications. As their approaches present some drawbacks when working in spatial domain, the main difficulty is still to identify objects if they do not occur at the expected position. In this paper, we present an improved fast and robust algorithm for detecting fire/smoke in a cluttered scene from a pair of cameras. The input images are first segmented according to a pre-determined disparity threshold map and the real-time disparities of fire. Binary image processing techniques are used to reject noise introduced into the segmented images through low-resolution disparity calculations which consequently can lead to the gain of clearer results. In order to reduce the false alarms, a new segmentation method used in this approach shows that segmented images using stereo-vision are more accurate than those segmented using color approach for the overall detection. The segmented images are then used for image feature extraction for a Fuzzy-neural network classifier to help the system to generate a warning in case fire/smoke is detected.

With the rapid development of information technology, personal computer privacy and permission management are becoming more and more important. Based on RSA encryption algorithm, we design a dynamic password encryption and codec algorithm, and propose a mechanism on computer access permission management which is capable of dealing with situations both online and offline. In the offline mode, administrators can authenticate users by matching their contact information to that registered in administrators’ mobile terminal. Generated by the co-work of a personal computer and a mobile terminal, the dynamic password makes cracking the password a trickier task. Permission control information is also added into the dynamic password, and file filter system will be loaded once the screen is successfully unlocked, so as to protect private directories or files from being accessed without authorization. In online mode, the system provides real-time video for identity verification, which makes the system more secure and convenient. Experiment results show that this dynamic password based mechanism on computer access permission management is efficient in dealing with existing problems in personal privacy and access permission management.

Computer network virus has been manufactured in bulk, which can affect the normal work and study of people, and therefore the defense and detection of computer network virus should be concerned, advanced defense ability of computer network virus under the environment of computer internet can be improved. Firstly, the basic characteristics of computer network virus are analyzed. Secondly, main computer network virus propagation models are studied. Thirdly, active defense technology and detection model of computer network virus are established based on supported vector machine, and corresponding algorithm procedure is constructed. Finally, the simulation experiments are carried out, and results show that the detection model can obtain better detection effect of the computer network virus.

본 논문에서는 PID 알고리즘을 이용하는 온도제어기의 가상적 튜닝 기법을 제안한다. 제어대상의 수학적 표현 을 이용하여 컴퓨터에서의 가상적 시뮬레이션을 활용하였다. 컴퓨터의 상세한 데이터 분석을 통하여 PID 알고리즘의 이득을 정확하게 구하는 기법을 도입하였고 기존의 실험적 튜닝 결과보다 우수한 성능을 검증하였다. 또한 실제의 제 어대상에서 실시하는 튜닝 실험을 대체하는 장점이 있어 시간적 공간적 제한이 전혀 없다. 제어대상을 실제 가동하는 튜닝 실험은 그 과정에서 나타나는 자세한 데이터를 확인할 수 없다. 실험의 정확성을 보장할 수 없으며 그 결과를 즉시 확인할 수도 없었다. 제안하는 기법을 통해 튜닝의 모든 과정을 컴퓨터에서 정확하게 확인할 수 있으며 발생하 는 문제의 원인도 분석할 수 있다.

In this paper, we propose a virtual tuning technique for a temperature controller using the PID algorithm. Virtual simulation on a computer was used using the mathematical expression of the control object. A technique for accurately calculating the gain of the PID algorithm was introduced through detailed computer data analysis, and superior performance compared to conventional experimental tuning results was verified. In addition, it has the advantage of replacing tuning experiments conducted on actual control subjects, so there are no temporal or spatial limitations. Tuning experiments that actually operate the control object do not show detailed data that appears during the process. The accuracy of the experiment could not be guaranteed, and the results could not be confirmed immediately. Through the proposed technique, the entire tuning process can be accurately checked on a computer and the cause of problems that occur can also be analyzed.

We propose a finger detection algorithm for computer mouse control to control the most commonly actions of a computer mouse(left, right and double click, scroll up and down then we add open and close, minimize and maximize a window, control the mouse.) We use a built-in web camera to control the mouse tasks. We detected, segment, then recognize the hand in our previous papers [1, 2]. The user will be able to interact with the computer with the number of fingers detected.

자연에 존재하는 연속량의 데이터는 디지털화 될 때 숫자로 변환된다. 이때 부딪치는 일반적인 문제는 완전히 통합되지 않았거나 잘못 통합된 표본 추출의 결과로 정보를 잃어버리는 앨리어싱(Aliasing) 현상이 일어나게 된다. 현재 일반 사용자가 사용하는 PC기반의 모니터 해상도는 96PPI(Pixel ZPer Inch)밖에 제공하지 못한다. 이러한 저해상도에서 컴퓨터 그래픽 이미지 객체를 디스플레이 할 때 앨리어싱 현상이 자주 발생한다. 현재 PC 기반의 그래픽 하드웨어 구조의 변형없이 저해상도 모니터상에서 앨리어싱 현상이 발생하는 이미지를 기존의 계산 방법을 감소시키면서 앨리어싱 현상을 제거하는 기법이 필요하다. 본 연구에서는 이와 같이 앨리어싱 현상을 감소시켜 이미지 데이터의 품질을 향상시킬 수 있는 개선된 Anti-Aliasing 알고리즘을 제안한다.

This paper proposes an algorithm that increases the speed of generating a Fresnel hologram using a recursive addition operation covering the whole coordinate array of a digital hologram. The 3D object designed to calculate the digital hologram used the depth-map image produced by computer graphics (CG). The proposed algorithm is a technique that performs CGH (computer generated hologram) operation with only the recursive addition from the hologram's whole coordinates by analyzing the regularity between the 3D object and the digital hologram coordinates. The experimental results showed that the proposed algorithm increased operation speed by 30% over the technique using the conventional CGH equation.