• 한국컴퓨터정보학회논문지
• /
• 제23권1호
• /
• pp.41-48
• /
• 2018

Recently, surveillance systems are widely used, and one of the key technologies in this surveillance system is to recognize and track objects. In order to track a moving object robustly and efficiently in a complex environment, it is necessary to extract the feature points in the interesting object and to track the object using the feature points. In this paper, we propose a method to track interesting objects in real time by eliminating unnecessary information from objects, generating feature point descriptors using only key feature points, and reducing computational complexity for object recognition. Experimental results show that the proposed method is faster and more robust than conventional methods, and can accurately track objects in various environments.

• International Journal of Control, Automation, and Systems
• /
• 제1권1호
• /
• pp.119-126
• /
• 2003

The problem of tracking moving objects in a video stream is discussed in this pa-per. We discussed the popular technique of optical flow for moving object detection. Optical flow finds the velocity vectors at each pixel in the entire video scene. However, optical flow based methods require complex computations and are sensitive to noise. In this paper, we proposed a new method based on the Hough transform and on voting accumulation for improving the accuracy and reducing the computation time. Further, we applied the Boo-lean based edge detector for edge detection. Edge detection and segmentation are used to extract the moving objects in the image sequences and reduce the computation time of the CHT. The Boolean based edge detector provides accurate and very thin edges. The difference of the two edge maps with thin edges gives better localization of moving objects. The simulation results show that the proposed method improves the accuracy of finding the optical flow vectors and more accurately extracts moving objects' information. The process of edge detection and segmentation accurately find the location and areas of the real moving objects, and hence extracting moving information is very easy and accurate. The Combinatorial Hough Transform and voting accumulation based optical flow measures optical flow vectors accurately. The direction of moving objects is also accurately measured.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2007년도 추계학술대회 논문집
• /
• pp.1913-1919
• /
• 2007

Substantive provisions of the concept of an estimation and safety of complex technical systems are envisaged. New problems are assume orientation to use of the formalized methods of an estimation of residual resources of reliability of objects, and also development of other methodological base in creation of complex technical systems that is connected with detailed elaboration of attention to a safety at all stages of creation of systems: from designing until operation. In this connection existing large objects should be provided by the developed systems of engineering monitoring and diagnostics.

• 천문학회보
• /
• 제35권2호
• /
• pp.72.1-72.1
• /
• 2010

We present infrared and millimeter observations of the active star-forming complex W51. A $1.25\;deg\times1.00\;deg$ region that includes the W51 complex was covered in the J = 2 - 1 transition of the $^{12}CO$ and $^{13}CO$ molecules with the University of Arizona Heinrich Hertz Submillimeter Telescope. We use a statistical equilibrium code to estimate physical properties of the molecular gas. Using Spitzer data we identify young stellar objects (YSOs) and fit model spectral energy distributions to these sources and constrain their physical properties. We compare the molecular cloud morphology with the distribution of infrared and radio continuum sources and find associations between molecular clouds and YSOs. We estimate that about 1% of the cloud mass is currently in YSOs.

• Steel and Composite Structures
• /
• 제49권1호
• /
• pp.31-45
• /
• 2023

The network theory studies interconnection between discrete objects to find about the behavior of a collection of objects. Also, nanomaterials are a collection of discrete atoms interconnected together to perform a specific task of mechanical or/and electrical type. Therefore, it is reasonable to use the network theory in the study of behavior of super-molecule in sport nano-scale. In the current study, we aim to examine vibrational behavior of spherical nanostructured composite with different geometrical and materials properties. In this regard, a specific shear deformation displacement theory, classical elasticity theory and analytical solution to find the natural frequency of the spherical nano-composite sport structure equipment. The analytical results are validated by comparison to finite element (FE). Further, a detail comprehensive results of frequency variations are presented in terms of different parameters. It is revealed that the current methodology provides accurate results in comparison to FE results. On the other hand, different geometrical and weight fraction have influential role in determining frequency of the structure.

• 한국콘텐츠학회:학술대회논문집
• /
• 한국콘텐츠학회 2003년도 춘계종합학술대회논문집
• /
• pp.426-429
• /
• 2003

본 논문에서는 3차원 물체의 인식을 위한 표면 분류시 그 임계치를 선정하는 방법에 대해 제안하고자 한다. 특히 보다 세밀하고 복잡한 물체의 표현을 위해 사용하여 왔던 평균 곡률과 가우스곡률이 가지고 있던 문제점인 임계치 선정 문제를 통계적 방법에 의해 해결하는 방법을 제안하고자 한다. 끝으로 본 논문의 유용성을 실험에 의해 입증하였다.

• 로봇학회논문지
• /
• 제10권1호
• /
• pp.33-41
• /
• 2015

Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
• /
• pp.285-292
• /
• 2002

A cluster tool for semiconductor manufacturing is an integrated device that consists of several single wafer processing modules and a wafer transport module based on a robot. The distributed module controllers are integrated by an inter-module communication network and coordinated by a centralized controller, called a cluster tool controller (CTC). Since the CTC monitors and coordinates the distributed complex module controllers for advanced process control, complex commuication messaging and services between the CTC and the module controllers are required. A SEMI standard, CTMC(Cluster Tool Module Communication), specifies application-level communication service requirements for inter-module communication. We propose the use of high-level fieldbuses, for instance. PROFIBUS-FMS, for implementing CTMC since the high-level fieldbuses are well suited for complex real-time distributed manufacturing control applications. We present a way of implementing CTMC using PROFIBUS-FMS as the communication enabler. We first propose improvements of a key object of CTMC for material transfer and the part transfer protocol to meet the functional requirements of modem advanced cluster tools. We also discuss mapping objects and services of CTMC to PROFIBUS-FMS communication objects and services. Finally, we explain how to implement the mappings.

• 정보기술과데이타베이스저널
• /
• 제6권1호
• /
• pp.1-13
• /
• 1999

The modeling components in the object-oriented paradigm are based on the object, not the structured function or procedure. That is, in the past, when one wanted to solve problems, he would describe the solution procedure. However, the object-oriented paradigm includes the concepts that solve problems through interaction between objects. The object-oriented model is constructed by describing the relationship between object to represent the real world. As in object-oriented model the relationships between objects increase, the control of objects caused by their insertions, deletions, and modifications comes to be very complex and difficult. Because the loss of the referential integrity happens and the object reusability is reduced. For these reasons, the necessity of the control of objects and the visualization of the relationships between them is required. In order that we design a database necessary to implement Object Browser that has functionalities to visualize Java objects and to perform the query processing in Java object modeling, in this paper we show the processes for EER modeling on Java object and its transformation into relational database schema. In addition we implement Java Object Parser that parses Java object and inserts the parsed results into the implemented database.

• 정보과학회 컴퓨팅의 실제 논문지
• /
• 제22권8호
• /
• pp.357-362
• /
• 2016

소셜 네트워크나 바이오 네트워크는 인터랙션이 가능한 오브젝트들이 관계를 맺음으로써 형성되는 복잡 네트워크이다. 실세계에 존재하는 복잡 네트워크는 커뮤니티 구조로 구성되어 있으며, 이 커뮤니티 구조를 자동으로 발견하는 것은 그 네트워크를 제어하고 이해하는데 있어서 중요한 기술이다. 하지만 이런 네트워크들은 시간에 따라 오브젝트들의 인터랙션에 의해 그 네트워크의 구조와 위상이 불특정하게 변화한다. 이런 동적 네트워크에서 노드들 간에 인터랙션을 기반으로 한 커뮤니티 구조를 발견하는 것은 높은 시간 복잡도 연산이 요구되며, 반복된 계산을 비효율적으로 처리하는 문제점이 있다. 따라서 본 연구에서는 동적 네트워크에서 인터랙션 기반 커뮤니티 구조를 점진적으로 발견하는 기법을 제안한다. 제안하는 기법은 이전 네트워크에서 변화한 요소들을 인지하고, 이전 커뮤니티 그룹 구조를 점진적으로 재활용함으로써 효율적인 커뮤니티 발견이 가능하다.