• Journal of the Korea Society of Computer and Information
• /
• v.28 no.1
• /
• pp.93-101
• /
• 2023

In this paper, we propose a method of creating a 3D bounding box for an object using a vanishing point to increase the accuracy of object recognition in an image when recognizing an traffic object using a video camera. Recently, when vehicles captured by a traffic video camera is to be detected using artificial intelligence, this 3D bounding box generation algorithm is applied. The vertical vanishing point (VP1) and horizontal vanishing point (VP2) are derived by analyzing the camera installation angle and the direction of the image captured by the camera, and based on this, the moving object in the video subject to analysis is specified. If this algorithm is applied, it is easy to detect object information such as the location, type, and size of the detected object, and when applied to a moving type such as a car, it is tracked to determine the location, coordinates, movement speed, and direction of each object by tracking it. Able to know. As a result of application to actual roads, tracking improved by 10%, in particular, the recognition rate and tracking of shaded areas (extremely small vehicle parts hidden by large cars) improved by 100%, and traffic data analysis accuracy was improved.

• Convergence Security Journal
• /
• v.6 no.4
• /
• pp.91-99
• /
• 2006

Generally, a study of web caching is conducted on a performance improvement with structural approaches and a new hybrid method using existing methods, and studies on caching method itself. And existing analysis of reference-characteristic are conducted on a history analysis and a preference of users, a view point of data mining by log analysis. In this study, we analyze the reference-characteristic of web object on a view point of a characteristic of probability-distribution and a mean value of lifetime of a web-object. And using this result, we propose the new method for a performance improvement of a web-caching.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.1
• /
• pp.99-104
• /
• 2009

This article describes the analysis of stable grasping for multi-fingered robot. An analysis method of stable grasping, which is based on the three-dimensional acceleration convex polytope, is proposed. This method is derived from combining dynamic equations governing object motion and robot motion, force relationship and acceleration relationship between robot fingers and object's gravity center through contact condition, and constraint equations for satisfying no-slip conditions at every contact points. After mapping no-slip condition to torque space, we derived intersected region of given torque bounds and the mapped region in torque space so that the intersected region in torque space guarantees no excessive torque as well as no-slip at the contact points. The intersected region in torque space is mapped to an acceleration convex polytope corresponding to the maximum acceleration boundaries which can be exerted by the robot fingers under the given individual bounds of each joints torque and without causing slip at the contacts. As will be shown through the analysis and examples, the stable grasping depends on the joint driving torque limits, the posture and the mass of robot fingers, the configuration and the mass of an object, the grasp position, the friction coefficients between the object surface and finger end-effectors.

• Communications for Statistical Applications and Methods
• /
• v.30 no.1
• /
• pp.37-48
• /
• 2023

Shape analysis is a method for measuring, describing and comparing the shape of objects in geometric space. An important aspect is to obtain Procrustes distance based on least square method. We note that the shape is all the geometrical information that remains when location, scale and rotational effects are filtered out from an object. However, and unfortunately, when we cannot measure some landmarks which are some biologically or geometrically meaningful points of any object, it is not possible to measure the variation of all shapes of an object, including that of the incomplete object. Hence, we need to replace the missing landmarks. In particular, Albers and Gower (2010) studied the missing rows of configurations in Procrustes analysis. They noted that the convergence of their approach can be quite slow. In this study, alternatively, we derive an algorithm for estimating the missing landmarks based on the pre-shapes. The pre-shape is invariant under the location and scaling of the original configuration with the centroid size of the pre-shape being one. Therefore we expect that we can reduce the amount of total computing time for obtaining the estimate of the missing landmarks.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.1243-1244
• /
• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Journal of the military operations research society of Korea
• /
• v.22 no.1
• /
• pp.67-80
• /
• 1996

Artificial Intelligence(AI) techniques and Object-Oriented(OO) techniques contribute to the simulation modeling of the complex systems. AI techniques are suitable to model human reasoning in the simulation. While OO techniques have advantages of re-usability, maintainability and extendability of the software. Thus, in this paper, we design a knowledge-based object-oriented simulation model, particularly for the logistics analysis of military armor vehicles. The simulation model consists of three modules i.e., scenario, simulation mechanism, and inference engine. The model is designed within the OO paradigm and implemented by using the C++ language. An example case of using the model for the logistic analysis is included.

• Korean Journal of Remote Sensing
• /
• v.33 no.6_3
• /
• pp.1187-1196
• /
• 2017

Despite the continuing effort to estimate the value of function and services of ecosystem, most of the researches has used low and medium resolution satellite imagery such as MODIS or Landsat. It means that the researches to measure the ecosystem service value using VHR (Very High Resolution) satellite imagery have not been performed much, while the source of available VHR imagery is increasing. Thus, the aim of this study is to estimate and compare the result of ecosystem service value over Sejong city, S. Korea, which is one of the rapidly changed city, through the pixel-based and object-based classification analysis using VHR KOMPSAT-3 images, for more specific and precise information. In the result of the classification, forest and grassland were underestimated while agriculture and urban were overestimated in the pixel-based result compared to the object-based result. Furthermore, bare soil area was presented contrasting result that was increased in the pixel-based result, however, decreased in the object-based result. Using those results, ecosystem service values were estimated. The annual ecosystem service values in 2014 were $8.18 million USD(pixel-based) and $8.63 million USD(object-based), however, decreased to $7.80 million USD(pixel-based) and $8.62 million USD(object-based) in 2016. It is expected to use those results as a preliminary data when to make sustainable development plan and policy to improve the quality of life in the local level.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.3
• /
• pp.622-632
• /
• 1999

As the complexity of software development is increasing due to networking, multimedia, and diverse system architecture, the need for effective software development methodology is increasing. Especially, due to software standard and internalization of software market, it is necessary to accept international quality such as ISO 9000-3. In addition, object oriented development methodology is required due to rapid propagation of OO technology and standardization. Recently, UML was accepted by the OMG as standard object-oriented modeling language for distributed environment. When we UML was accepted by the OMG as standard object-oriented modeling language for distributed environment. When we develop Java and CORBA-based software, often UML is applied to Java and CORBA-based projects. However, current structural or OMT-based object-oriented methodologies. In this paper, we proposed UML-based development and concrete guidelines for each phase in order to apply UML to software development practically and effectively. Also, we define the transition guidelines and semantics between various development tasks. In addition, the analysis and design techniques of user interface and system development techniques needed in Web application development are presented.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.9
• /
• pp.49-55
• /
• 2019

This paper presents a marker image evaluation method based on analysis of object distribution in images and classification of images with repetitive patterns for effective marker-based augmented reality (AR) system development. We measure the variance of feature point coordinates to distinguish marker images that are vulnerable to occlusion, since object distribution affects object tracking performance according to partial occlusion in the images. Moreover, we propose a method to classify images suitable for object recognition and tracking based on the fact that the distributions of descriptor vectors among general images and repetitive-pattern images are significantly different. Comprehensive experiments for marker images confirm that the proposed marker image evaluation method distinguishes images vulnerable to occlusion and repetitive-pattern images very well. Furthermore, we suggest that scale-invariant feature transform (SIFT) is superior to speeded up robust features (SURF) in terms of object tracking in marker images. The proposed method provides users with suitability information for various images, and it helps AR systems to be realized more effectively.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.6
• /
• pp.63-70
• /
• 2013

In accordance with the advancement of IT, application systems with various and complex functions are being required. Such application systems are typically built based on database in order to manage data efficiently. But most object-oriented analysis design methodologies for developing web application systems have not been providing interconnections with the database. Since the requirements regarding the security issues increased, the importance of security has become emphasized. However, since the security is usually considered at the last step of development, it is difficult to apply the security during the whole process of system development, from the requirement analysis to implementation. Therefore, this paper suggests an object-oriented analysis and design methodology for secure database design from the requirement analysis to implementation. This object-oriented analysis and design methodology for secure database design offers correlations with database that most existing object-oriented analysis and design methodologies could not provide. It also uses UMLsec, the modeling language, to apply security into database design. In addition, in order to implement security, RBAC (Role Based Access Control) of relational database is used.