• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1050-1061
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• 2000

This paper presents a new object model, LOM(Lightweight Object Model) and an implementation method for the distributed trader in heterogeneous distributed computing environment including mobile network. Trader is third party object that enables clients to find suitable servers, which provide the most appropriate services to client in distributed environment including dynamic reconfiguration of services and servers. Trading service requires simpler and more specific object model than genetic object models which provide richer multimedia data types and semantic characteristics with complex data structures. LOM supports a new reference attribute type instead of the relationship, inheritance and composite attribute types of the general object oriented models and so LOM has simple data structures. Also in LOM, the modelling step includes specifying of the information about users and the access right to objects for security in the mobile environment and development of the distributed storage for trading service. Also, we propose and implementation method of the distributed trader, which integrates the LOM-information object model and the OMG (object Management Group) computational object model.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.125-131
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• 1999

In this paper, the algorithms which can track the two dimensional moving circular object using simple vision system are described. In order to track the moving object, the process of finding the object feature points - such as centroid of the object, corner points, area - is indispensable. With the assumption of two-dimensional circular moving object, the centroid of the circular object is computed from three points on the object circumference. Different kinds of algorithms for computing three edge points - simple x directional detection method, stick method. T-shape method are suggested. Through the computer simulation and experiments, three algorithms are compared from the viewpoint of detection accuracy and computational time efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5419-5435
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• 2017

The construction of panoramic images on smartphones and low-powered devices is a challenging task. In this paper, we propose a new approach for smoothly stitching images on mobile phones in the presence of moving objects in the scene. Our main contributions include handling moving object problems, reducing processing time, and generating rectangular panoramic images. First, unique and robust feature points are extracted using fast ORB method and a feature matching technique is applied to match the extracted feature points. After obtaining good matched feature points, we employ the non-deterministic RANSAC algorithm to discard wrong matches, and the hommography transformation matrix parameters are estimated with the algorithm. Afterward, we determine precise overlap regions of neighboring images and calculate their absolute differences. Then, thresholding operation and noise removal filtering are applied to create a mask of possible moving object regions. Sequentially, an optimal seam is estimated using dynamic programming algorithm, and a combination of linear blending with the mask information is applied to avoid seam transition and ghosting artifacts. Finally, image-cropping operation is utilized to obtain a rectangular boundary image from the stitched image. Experiments demonstrate that our method is able to produce panoramic images quickly despite the existence of moving objects.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.5
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• pp.547-553
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• 2021

Dynamic object recognition is an important task for autonomous vehicles. Since dynamic objects exhibit a higher collision risk than static objects, our own trajectories should be planned to match the future state of moving elements in the scene. Time information such as optical flow can be used to recognize movement. Existing optical flow calculations are based only on camera sensors and are prone to misunderstanding in low light conditions. In this regard, to improve recognition performance in low-light environments, we applied a normalization filter and a correction function for Gamma Value to the input images. The low light quality improvement algorithm can be applied to confirm the more accurate detection of Object's Bounding Box for the vehicle. It was confirmed that there is an important in object recognition through image prepocessing and deep learning using YOLO.

• The Journal of Society for e-Business Studies
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• v.4 no.1
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• pp.145-157
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• 1999

The challenge is to maximize the time-to-market benefits of concurrent engineering while maintaining control of data and distributing it automatically to the people who need it when they need it. The way PDM systems cope with this challenge is that master data is held only once in a secure vault where its integrity can be assured and all changes to it monitored, controlled and recorded. The structure of PDM is various from vendor, but they have common module. That is PDM and it is most important. The goal is to design the workflow in PDM using object-oriented modeling method. The past methods have concentrated on the flow between workflow engine and agent, but this paper will focus on task. We will model task as individual object. This paper uses OMT(Object Modeling Technique) by James Rumbaugh for base modeling tool and uses DCOM(Distributed Component Object Model) for base ORB(Object Request Broker). Research object is to design the static object model, to design state change by dynamic model and to design data transition by functional model.

• Journal of Platform Technology
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• v.8 no.4
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• pp.11-19
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• 2020

In an autonomous driving environment, dynamic recognition of objects is essential as the situation changes in real time. In addition, as the number of sensors and control modules built into an autonomous vehicle increases, the amount of data the central control unit has to process also rapidly increases. By minimizing the output data from the sensor, the load on the central control unit can be reduced. This study proposes a dynamic object recognition algorithm solely using the embedded processor on a LiDAR sensor. While there are open source algorithms to process the point cloud output from LiDAR sensors, most require a separate high-performance processor. Since the embedded processors installed in LiDAR sensors often have resource constraints, it is essential to optimize the algorithm for efficiency. In this study, an embedded processor based object recognition algorithm was developed for autonomous vehicles, and the correlation between the size of the point clouds and processing time was analyzed. The proposed object recognition algorithm evaluated that the processing time directly increased with the size of the point cloud, with the processor stalling at a specific point if the point cloud size is beyond the threshold

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.1013-1024
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• 1997

In the traditional object modeling methodologies, the object model can be said as formal since it has been based on rich semantic model. But almost of all methodolgies lack in formality the dyamic model and modeling process. Dynamic model cannot represent exctly the timing constraints and the interaction among the objects, which are very important features in real-time and multimedia system. In this paper, we formalize the synamic moedl and modeling proxess based on object behavior and state. This model defines the object state space using the concepts in algebra stucture and defines the object behavior func-tion. Also this model can formalize object kifecycle and conurrency among the objects usint the temporal logiction. Also this model can frlmaize object lifecycle and conurrency among the objects using the tempral logic and behavior founction. We apply firing rules to behacior function for modeling the dependency of interaction among the objescts.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.817-833
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• 1996

Most object-oriented analysis and design methodologies are based on structured analysis and information modeling and are using for intuitive analysis and design models based on object-oriented programming languages. Therefore there are many problems such as when a system is implemented incorrect semantics and inconsistency between models.This paper submits a decomposition and design method for object, dynamic and functional module of the methodology of a new system development life-cycle. Thus, we present a new system development life cycle, and suggestsa object-oriented design methodand standards of module decomposition for the decomposition of object, dynamic, functional models due to object-oriented design procedures and specifications. This proposed method enables developers to reflect user's software requirements conveniently. We prove the validity and practicality of this object-oriented design method through implementing a real-system.

• Journal of the HCI Society of Korea
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• v.6 no.1
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• pp.9-16
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• 2011

The previous researches of 3D object modeling have been performed in a limited environment where a target object only exists. However, in order to model an object in the real environment, we need to consider a dynamic environment, which has various objects and a frequently changing background. Therefore, this paper presents a segmentation and tracking method for a foreground which includes a target object in the dynamic environment. By using depth information than color information, the foreground region can be segmented and tracked more robustly. In addition, the foreground region can be tracked on the sequential images by referring depth distributions of the foreground region because both the position and the status in the consecutive images of the foreground region are almost unchanged. Experimental results show that our proposed method can robustly segment and track the foreground region in various conditions of the real environment. Moreover, as an application of the proposed method, it is presented a method for modeling an object extracting the object regions from the foreground region that is segmented and tracked.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1994-1999
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• 2003

This paper discusses dynamic characteristics of motion of a pair of multi-degrees of freedom robot fingers executing grasp of a rigid object and controlling its orientation with the aid of rolling contacts. In particular, the discussions are focused on a problem of gain-tuning of sensory feedback signals proposed from the viewpoint of sensorymotor coordination, which consist of a feedforward term, a feedback term for controlling rotational moment of the object, and another term for controlling its rotational angle. It is found through computer simulations of the overall fingersobject dynamics subject to rolling contact constraints that some dynamic characteristics of torque-angular velocity relation may play an important role likely as reported by experimental results in muscle physiology and therefore selection of damping gains in angular velocity feedback depending on the guess of object mass is crucial. Finally, a guidance of gain-tuning in each feedback term is suggested and its validity is discussed by various computer simulations.