• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.960-964
• /
• 2004

During system resource improvement process that based on Object-Oriented technology could be affect to the continuous system performance if lack appropriate management and control objects mechanism. This paper proposes a methodology to support continuous system performance and its stability. The adoption is based on Java Container Framework and Collections Framework for object collection. Also includes Software Engineering, Object Migration and Multiple Class Loaders mechanism accommodate to construct Continuous Migration Container (CMC). CMC is a runtime environment provides interfaces for management and control to support upgrading object process. Upgrade object methodology of CMC can be divided into two phase are object equivalence checking and object migration process. Object equivalence checking include object behavior verification and functional conformance verification before object migration process. In addition, CMC use Multiple Class Loaders mechanism to support reload effected classes instead of state transfer in migration process while upgrading object. These operations are crucial for system stability and enhancement efficiency.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.14 no.2
• /
• pp.35-47
• /
• 2018

The 4th industrial revolution, digital image technology has developed beyond the limit of multimedia industry to advanced IT fusion and composite industry. Particularly, application technology related to HCI element algorithm in 3D image object recognition field is actively developed. 3D image object recognition technology evolved into intelligent image sensing and recognition technology through 3D modeling. In particular, image recognition technology has been actively studied in image processing using object recognition recognition processing, face recognition, object recognition, and 3D object recognition. In this paper, we propose a research method of human factor 3D image recognition technology applying human factor algorithm for 3D object recognition. 1. Methods of 3D object recognition using 3D modeling, image system analysis, design and human cognitive technology analysis 2. We propose a 3D object recognition parameter estimation method using FACS algorithm and optimal object recognition measurement method. In this paper, we propose a method to effectively evaluate psychological research techniques using 3D image objects. We studied the 3D 3D recognition and applied the result to the object recognition element to extract and study the characteristic points of the recognition technology.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.11 no.3
• /
• pp.99-112
• /
• 2015

Digital imaging technology has advanced beyond the limits of the multimedia industry IT convergence, and to develop a complex industry, particularly in the field of object recognition, face smart-phones associated with various Application technology are being actively researched. Recently, face recognition technology is evolving into an intelligent object recognition through image recognition technology, detection technology, the detection object recognition through image recognition processing techniques applied technology is applied to the IP camera through the 3D image object recognition technology Face Recognition been actively studied. In this paper, we first look at the essential human factor, technical factors and trends about the technology of the human object recognition based SPFACS(Smile Progress Facial Action Coding System)study measures the smile detection technology recognizes multi-faceted object recognition. Study Method: 1)Human cognitive skills necessary to analyze the 3D object imaging system was designed. 2)3D object recognition, face detection parameter identification and optimal measurement method using the AAM algorithm inside the proposals and 3)Face recognition objects (Face recognition Technology) to apply the result to the recognition of the person's teeth area detecting expression recognition demonstrated by the effect of extracting the feature points.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.12 no.4
• /
• pp.1-12
• /
• 2016

Digital imaging technology has developed into a state-of-the-art IT convergence, composite industry beyond the limits of the multimedia industry, especially in the field of smart object recognition, face - Application developed various techniques have been actively studied in conjunction with the phone. Recently, face recognition technology through the object recognition technology and evolved into intelligent video detection recognition technology, image recognition technology object detection recognition process applies to skills through is applied to the IP camera, the image object recognition technology with face recognition and active research have. In this paper, we first propose the necessary technical elements of the human factor technology trends and look at the human object recognition based spFACS (Smile Progress Facial Action Coding System) for detecting smiles study plan of the image recognition technology recognizes objects. Study scheme 1). ASM algorithm. By suggesting ways to effectively evaluate psychological research skills through the image object 2). By applying the result via the face recognition object to the tooth area it is detected in accordance with the recognized facial expression recognition of a person demonstrated the effect of extracting the feature points.

• Asia pacific journal of information systems
• /
• v.10 no.2
• /
• pp.1-22
• /
• 2000

This paper presents an exploratory research on the application of the Technology Acceptance Model(TAM) to the domain of object orientation to investigate the validity of TAM in the perspective of its causal relationships. In the Management Information Systems(MIS) area, TAM has been applied to computer usage behavior as a specific technology adoption model. This paper also suggests the factors that affect the technology acceptance of object orientation in U.S. organizations through a modified TAM. Two major research questions are addressed. First, this research investigates the effect of these external variables on the dependent variable, the actual usage of object orientation in the viewpoint of knowledge interaction between structured methods and object orientation. Second, is TAM valid for the technology acceptance of object orientation in terms of its causal relationships? This study empirically explores the impact of the external variables on the level of actual usage of object orientation via the mediating variables in TAM. A structured questionnaire is administered to Data Processing Management Association(DPMA) professionals in US. The result of this study reveals one important contradictory finding that is not consistent with expectations based on related theory. TAM does not accommodate the technology acceptance of object orientation perhaps because object orientation is a complex and organization-level adoptive technology or the measures for the mediating constructs in TAM may not be appropriate in industry settings.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1999.06a
• /
• pp.165.1-170
• /
• 1999

Object segmentation fro natural video scenes has recently become one of very active research to pics due to the object-based video coding standard MPEG-4. Object detection and isolation is also useful for object-based indexing and search of video content, which is a goal of the emerging new standard, MPEG-7. In this paper, an automatic segmentation method of moving objects in image sequence is presented which is applicable to multimedia content authoring for MPEG-4, and two different segmentation approaches suitable for surveillance applications are addressed in raw data domain and compressed bitstream domains. We also propose an object-based video description scheme based on object segmentation for video indexing purposes.

• International Journal of Advanced Culture Technology
• /
• v.7 no.4
• /
• pp.229-235
• /
• 2019

Due to the development of video and optical technology today, video equipments are being used in a variety of fields such as identification, security maintenance, and factory automation systems that generate products. In this paper, we investigate an algorithm that effectively recognizes an experimental object in an input image with a partial problem due to the mechanical problem of the input imaging device. The object recognition algorithm proposed in this paper moves and rotates the vertices constituting the outline of the experimental object to the positions of the respective vertices constituting the outline of the DB model. Then, the discordance values between the moved and rotated experimental object and the corresponding DB model are calculated, and the minimum discordance value is selected. This minimum value is the final discordance value between the experimental object and the corresponding DB model, and the DB model with the minimum discordance value is selected as the recognition result for the experimental object. The proposed object recognition method obtains satisfactory recognition results using only partial information of the experimental object.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2379-2384
• /
• 2005

We propose a novel method for object recognition using the smart tag system with a stereo vision on a pan-tilt mechanism. We developed a smart tag which included IRED device. The smart tag is attached onto the object. We also developed a stereo vision system which pans and tilts for the object image to be the centered on each whole image view. A Stereo vision system on the pan-tilt mechanism can map the position of IRED to the robot coordinate system by using pan-tilt angles. And then, to map the size and pose of the object for the robot to coordinate the system, we used a simple model-based vision algorithm. To increase the possibility of tag-based object recognition, we implemented our approach by using as easy and simple techniques as possible.

• The Journal of Information Systems
• /
• v.10 no.1
• /
• pp.97-126
• /
• 2001

Object-orientation has been proposed as a promising software process innovation to improve software productivity and quality. It has not been understood clearly, however, what factors influences the diffusion of object-oriented technology in organizations. A research model was formulated and hypotheses were generated based on the literature of information technology implementation and software process innovation. To test the research hypotheses, a questionnaire survey was conducted. The results based on 121 responses from Korean companies revealed that project characteristics, use of external experts, and number of development projects are significantly related to the diffusion of object-oriented analysis and design and object-oriented programming. Innovation champion is positively related to the diffusion of object-oriented analysis and design, whereas it is not related to the diffusion of object-oriented programming language. Only project complexity was significantly related to the diffusion of visual programming language. On the other hand, organizational size was not significantly related to any object-oriented technology in this study.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.204-206
• /
• 2003

In order to utilize remote sensed images effectively, a lot of image classification methods are suggested for many years. But, the accuracy of traditional methods based on pixel-based classification is not high in general. In this study, object oriented classification based on image segmentation is used to classify Landsat images. A necessary prerequisite for object oriented image classification is successful image segmentation. Object oriented image classification, which is based on fuzzy logic, allows the integration of a broad spectrum of different object features, such as spectral values , shape and texture. Landsat images are divided into urban, agriculture, forest, grassland, wetland, barren and water in sochon-gun, Chungcheongnam-do using object oriented classification algorithms in this paper. Preliminary results will help to perform an automatic image classification in the future.