• International Journal of Precision Engineering and Manufacturing
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• v.5 no.1
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• pp.27-35
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• 2004

In the field of machine vision using a single camera mounted on a mobile robot, although the detection and tracking of moving objects from a moving observer, is complex and computationally demanding task. In this paper, we propose a new scheme for a mobile robot to track and capture a moving object using images of a camera. The system consists of the following modules: data acquisition, feature extraction and visual tracking, and trajectory generation. And a single camera is used as visual sensors to capture image sequences of a moving object. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.

• The Korean Journal of Community Living Science
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• v.17 no.4
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• pp.3-14
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• 2006

The purpose of this study is to find out the repercussion of mothers' quality of object relation and hope on their children's emotional and behavioral disorder level and satisfaction level on counseling. Participants were 112 children between ages of 6 and 12, and the 112 mothers of those children. Questionnaires for mothers were used to assess their object relation level, hope level, and counseling satisfaction level. Questionnaires for children were used to assess their depression and aggression level. Results were as follows: First, mothers with lower object relations had children with higher depression and aggression levels. Second, children of the mothers who scored higher object relation levels scored higher on the satisfaction level on counseling. Third, among the mother's object relation level, hope level, and counseling satisfaction level, the object relation level appeared to have the strongest repercussion on the child's emotional and behavioral problems. The results of this study can be used as a base material to improve the effect of play therapy for the children who have emotional and behavioral problems, on helping the children and their mothers to have positive object relations.

• Journal of the Korea Society of Computer and Information
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• v.22 no.5
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• pp.21-28
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• 2017

As technology related to digital imaging equipment is developed and generalized, digital imaging system is used for various purposes in fields of society. The object tracking technology from digital image data in real time is one of the core technologies required in various fields such as security system and robot system. Among the existing object tracking technologies, cam shift technology is a technique of tracking an object using color information of an object. Recently, digital image data using infrared camera functions are widely used due to various demands of digital image equipment. However, the existing cam shift method can not track objects in image data without color information. Our proposed tracking algorithm tracks the object by analyzing the color if valid color information exists in the digital image data, otherwise it generates the lightness feature information and tracks the object through it. The brightness feature information is generated from the ratio information of the width and the height of the area divided by the brightness. Experimental results shows that our tracking algorithm can track objects in real time not only in general image data including color information but also in image data captured by an infrared camera.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1236-1249
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• 2020

In a most recent object tracking research work, applying Convolutional Neural Network and Recurrent Neural Network-based strategies become relevant for resolving the noticeable challenges in it, like, occlusion, motion, object, and camera viewpoint variations, changing several targets, lighting variations. In this paper, the LSTM Network-based Tracking association method has proposed where the technique capable of real-time multi-object tracking by creating one of the useful LSTM networks that associated with tracking, which supports the long term tracking along with solving challenges. The LSTM network is a different neural network defined in Keras as a sequence of layers, where the Sequential classes would be a container for these layers. This purposing network structure builds with the integration of tracking association on Keras neural-network library. The tracking process has been associated with the LSTM Network feature learning output and obtained outstanding real-time detection and tracking performance. In this work, the main focus was learning trackable objects locations, appearance, and motion details, then predicting the feature location of objects on boxes according to their initial position. The performance of the joint object tracking system has shown that the LSTM network is more powerful and capable of working on a real-time multi-object tracking process.

• The Transactions of the Korea Information Processing Society
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• v.2 no.1
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• pp.1-11
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• 1995

Object-oriented database systems represent the complex data model of real- world and manage the complex data. An object manager handles the manipulation and access of all objects in object-oriented database management systems. In this paper, we not only propose the design rules of an object manager interface(OMI) which is specified the calling function and the semantics of an object manager for object-oriented query processing, but also implement the OMI based on the rules. The OMI implemented supports the independently developing environment of query processing and object management modules, and can be applicable to various applications, and also provides the efficient access method to users.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.35-41
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• 2012

This paper proposes a moving object detection algorithm for active camera system that can be applied to mobile robot and intelligent surveillance system. Most of moving object detection algorithms based on a stationary camera system. These algorithms used fixed surveillance system that does not consider the motion of the background or robot tracking system that track pre-learned object. Unlike the stationary camera system, the active camera system has a problem that is difficult to extract the moving object due to the error occurred by the movement of camera. In order to overcome this problem, the motion of the camera was compensated by using SURF and Pseudo Perspective model, and then the moving object is extracted efficiently using stochastic Label Cluster transport model. This method is possible to detect moving object because that minimizes effect of the background movement. Our approach proves robust and effective in terms of moving object detection in active camera system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3180-3199
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• 2013

While non-predefined object segmentation (NDOS) distinguishes an arbitrary self-assumed object from its background, predefined object segmentation (DOS) pre-specifies the target object. In this paper, a new and novel method to segment predefined objects is presented, by globally optimizing an orientation-based objective function that measures the fitness of the object boundary, in a discretized parameter space. A specific object is explicitly described by normalized discrete sets of boundary points and corresponding normal vectors with respect to its plane shape. The orientation factor provides robust distinctness for target objects. By considering the order of transformation elements, and their dependency on the derived over-segmentation outcome, the domain of translations and scales is efficiently discretized. A branch and bound algorithm is used to determine the transformation parameters of a shape model corresponding to a target object in an image. The results tested on the PASCAL dataset show a considerable achievement in solving complex backgrounds and unclear boundary images.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.760-765
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• 2009

Since the features in object-images such as color and shape cannot clearly express the characteristic of objects, those features lead to vagueness of object-image recognition. Recently there have been studied on object-image recognition based on knowledge base in order to reduce the vagueness. However, because images are represented by numerical information but knowledge bases are represented by conceptual information, combining two kinds of information is difficult. In this paper, we compose knowledge base by using ontology to reduce the gap between the two kinds of information, and propose a method for object-image recognition to reduce the vagueness by using information on inner-object. Moreover, we confirm the usefulness of the proposed method through the experiments on object-image recognition in fruit domain.

• The Transactions of the Korea Information Processing Society
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• v.2 no.3
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• pp.299-313
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• 1995

Object-Oriented design method decomposes the program into object that establish the relationship between objects. It is the technique of object centered decomposition unlike function oriented legacy system. Since existing Object- Oriented design method doesn't fully explain of the design method of module and decomposition, and need to implement the Object-Oriented software as a total system init. It has many problems that whole object design method and application programs should be analyzed for the understanding an Object-Oriented software component. Therefore, this study provides a procedure for Object-Oriented module design and criteria of decomposition to practically support the complex and large system development. Futhermore, it shows a consistency between design model and implementation through a case study applying these module decomposition criteria to the real system.

• 한국HCI학회:학술대회논문집
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• 2008.02c
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• pp.19-24
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• 2008

This paper presents a physically-based haptic rendering algorithm for a deformable object based on visual information about the intervention between a tool and a real object in a remote place. The physically-based model of a deformable object is created from the mechanical properties of the object and the captured image obtained with a CCD camera. When a slave system exerts manipulation tasks on a deformable object, the reaction force for haptic rendering is computed using boundary element method. Snakes algorithm is used to obtain the geometry information of a deformable object. The proposed haptic rendering algorithm can provide haptic feedback to a user without using a force transducer in a teleoperation system.