• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.243-253
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• 2002

These days, the application range of digital photogrammetry is being extended actively, so the great variety of research is being progressed about improvement of measurement accuracy. This method can acquisite a high analysis accuracy and can acquisite easily image. But, So this method require a much processing time and effort by increasing a data amount, as the automation of processing must be completed for efficiency improvement of processing. In this study, the automation of image processing stage is established for multi-image aquisition and analysis about a radio telescope. Also, the precise measurement and the accuracy on object were intended to be improved. As a result of this study, the accuracy on the object which demands precise measurement was enhanced from multi image analysis, and also the assembly accuracy of the object could be checked by precise measurement and curve fitting.

• Journal of IKEEE
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• v.26 no.3
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• pp.364-372
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• 2022

This paper proposes the design and implementation results for human and object classification systems utilizing frequency modulated continuous wave (FMCW) radar sensor. Such a system requires the process of radar sensor signal processing for multi-target detection and the process of deep learning for the classification of human and object. Since deep learning requires such a great amount of computation and data processing, the lightweight process is utmost essential. Therefore, binary neural network (BNN) structure was adopted, operating convolution neural network (CNN) computation in a binary condition. In addition, for the real-time operation, a hardware accelerator was implemented and verified via FPGA platform. Based on performance evaluation and verified results, it is confirmed that the accuracy for multi-target classification of 90.5%, reduced memory usage by 96.87% compared to CNN and the run time of 5ms are achieved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1121-1129
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• 2022

Object recognition is carried out using RGB images in various object recognition studies. However, RGB images in dark illumination environments or environments where target objects are occluded other objects cause poor object recognition performance. On the other hand, IR images provide strong object recognition performance in these environments because it detects infrared waves rather than visible illumination. In this paper, we propose an RGB-IR fusion model, high-frequency interchange network (HINet), which improves object recognition performance by combining only the strengths of RGB-IR image pairs. HINet connected two object detection models using a mutual high-frequency transfer (MHT) to interchange advantages between RGB-IR images. MHT converts each pair of RGB-IR images into a discrete cosine transform (DCT) spectrum domain to extract high-frequency information. The extracted high-frequency information is transmitted to each other's networks and utilized to improve object recognition performance. Experimental results show the superiority of the proposed network and present performance improvement of the multispectral object recognition task.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.120-134
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• 2000

In this paper we present a Distributed Object oriented Virtual computing Environment, called DOVE which consists of autonomous distributed objects interacting with one another via method invocations based on a distributed object model. DOVE appears to a user logically as a single virtual computer for a set of heterogeneous hosts connected by a network as if objects in remote site reside in one virtual computer. By supporting efficient parallelism, heterogeneity, group communication, single global name service and fault-tolerance, it provides a transparent and easy-to-use programming environment for parallel applications. Efficient parallelism is supported by diverse remote method invocation, multiple method invocation for object group, multi-threaded architecture and synchronization schemes. Heterogeneity is achieved by automatic data arshalling and unmarshalling, and an easy-to-use and transparent programming environment is provided by stub and skeleton objects generated by DOVE IDL compiler, object life control and naming service of object manager. Autonomy of distributed objects, multi-layered architecture and decentralized approaches in hierarchical naming service and object management make DOVE more extensible and scalable. Also,fault tolerance is provided by fault detection in object using a timeout mechanism, and fault notification using asynchronous exception handling methods

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.4
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• pp.344-365
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• 2009

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.458-470
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• 2006

This paper describes issues and consideration on authoring of interactive multi-view visual content based on MPEG-4. The issues include types of multi-view visual content; scene composition for rendering; functionalities for user-interaction; and multi-view visual content file format. The MPEG-4 standard, which aims to provide an object based audiovisual coding tool, has been developed to address the emerging needs from communications, interactive broadcasting as well as from mixed service models resulting from technological convergence. Due to the feature of object based coding, the use of MPEG-4 can resolve the format diversity problem of multi-view visual contents while providing high interactivity to users. Throughout this paper, we will present which issues need to be determined and how they can be realized by means of MPEG-4 Systems.

• Human Ecology Research
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• v.52 no.6
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• pp.573-586
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• 2014

The purpose of this study was to review the conceptual framework of social constructionism and critical social constructionism in the research area of multi-cultural family homes, using a literature review. Fopp argued that social constructionism had an objectivation problem that only considered the actor side as a policy object; therefore he suggested a weaker social constructionist perspective with moderate relativism and the application of feminist epistemology to marginal life for maximizing objectivity. This article explores a conceptual framework for studying the reality of housing of multi-cultural families in Korea in the light of constructionist ideas and presents a review of empirical positivist data to support the framework. Based on results, using the social constructionist framework, five contexts (structural, institutional, organizational, operational, and intersubjective) were reviewed and ideas were suggested to develop an appropriate future situation for multi-cultural family homes. For a weaker social constructionist framework, three National Survey of Multi-Cultural Family Homes data sets were reviewed to determine the real condition of multi-cultural family homes. Further, from a feminist perspective, the empirical data of marginalized multi-cultural family homes were reviewed from the perspectives of gender inequality of decision making, cultural adaptation, and differentiation in housing related areas. In conclusion, two perspectives were useful for understanding multi-cultural family housing in Korea but must be compensated with substantial empirical data for a holistic approach.

• Journal of Broadcast Engineering
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• v.13 no.3
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• pp.299-309
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• 2008

In this paper, we propose an algorithm for object generation from model-based 3-dimensional multi-viewpoint images using OpenGL rendering. In the first step, we preprocess a depth map image in order to get a three-dimensional coordinate which is sampled as a vertex information on OpenGL and has a z-value as depth information. Next, the Delaunay Triangulation algorithm is used to construct a polygon for texture-mapping using the vertex information. Finally, by mapping a texture image on the constructed polygon, we generate a viewpoint-adaptive object by calculating 3-dimensional coordinates on OpenGL.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.559-562
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• 2006

Existing 4D systems are using the 1:1 link system that directly links a schedule and a 3D model object. But considering that plant facility includes various kinds of schedule and 3D model object, this study suggests an improved link methodology of multi-selected objects and two-way link system for minimizing link errors which generated in case of multi-selected objects. For the link system, this study introduces a new concept called as interface board. Interface board can be used as an information center for representing all information of link items in the current project. It may be expected that 4D model can build an effective and rapid link system of plant project by this new approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2C
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• pp.181-187
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• 2012

Millimeter wave (MMW) readily penetrates fabrics, thus it can be used to detect objects concealed under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people in both indoors and outdoors. However, because of the diffraction limit and low signal level, the imaging system often suffers from low image quality. Therefore, suitable statistical analysis and computational processing would be required for automatic analysis of the images. In this paper, a real-time concealed object detection is addressed by means of the multi-level segmentation. The histogram of the image is modeled with a Gaussian mixture distribution, and hidden object areas are segmented by a multi-level scheme involving $k$-means, the expectation-maximization algorithm, and a decision rule. The complete algorithm has been implemented in C++ environments on a standard computer for a real-time process. Experimental and simulation results confirm that the implemented system can achieve the real-time detection of concealed objects.