• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.1-7
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• 2019

Recently, smart factories have attracted much attention as a result of the 4th Industrial Revolution. Existing factory automation technologies are generally designed for simple repetition without using vision sensors. Even small object assemblies are still dependent on manual work. To satisfy the needs for replacing the existing system with new technology such as bin picking and visual servoing, precision and real-time application should be core. Therefore in our work we focused on the core elements by using deep learning algorithm to detect and classify the target object for real-time and analyzing the object features. We chose YOLO CNN which is capable of real-time working and combining the two tasks as mentioned above though there are lots of good deep learning algorithms such as Mask R-CNN and Fast R-CNN. Then through the line and inside features extracted from target object, we can obtain final outline and estimate object posture.

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.475-505
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• 1998

With rapid progresses in information technologies, managing enterprise network resources as a whole becomes more important. Telecommunication Management Network (TMN) has been used to integrate network elements. TMN is complex to develop and manage because it has a centralized management service. Common Object Request Broker Architecture (CORBA) can overcome this complexity by the use of transparent distributed object processing mechanism. Therefore, the main objective of this paper is to integrate TMN service with CORBA. A network management repository is built for this integration. In addition, a prototype that can partially support network management service is implemented to illustrate the usefulness of this repository.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2430-2436
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• 2013

This study suggests a method of detecting the still object, which becomes a cause of danger within the crossroad. The Inverse Perspective Transform was performed in order to make the object size consistent by being inputted the real-time image from CCTV that is installed within the crossroad. It established the detection area in the image with the perspective transform and generated the adaptative background image with the use of the moving information on object. The detection of the stop object was detected the candidate region of the stop object by using the background-image differential method. To grasp the appearance of truth on the detected candidate region, a method is proposed that uses the gradient information on image and EHD(Edge Histogram Descriptor). To examine performance of the suggested algorithm, it experimented by storing the images in the commuting time and the daytime through DVR, which is installed on the cross street. As a result of experiment, it could efficiently detect the stop vehicle within the detection region inside the crossroad. The processing speed is shown in 13~18 frame per second according to the area of the detection region, thereby being judged to likely have no problem about the real-time processing.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.2
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• pp.93-100
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• 2014

3D object recognition using only 2D images is a difficult work because each images are generated different to according to the view direction of cameras. Because SIFT algorithm defines the local features of the projected images, recognition result is particularly limited in case of input images with strong perspective transformation. In this paper, we propose the object recognition method that improves SIFT algorithm by using several sequential images captured from rotating 3D object around a rotation axis. We use the geometric relationship between adjacent images and merge several images into a generated feature space during recognizing object. To clarify effectiveness of the proposed algorithm, we keep constantly the camera position and illumination conditions. This method can recognize the appearance of 3D objects that previous approach can not recognize with usually SIFT algorithm.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.580-591
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• 2019

This paper focuses on to improving object detection performance using the camera and LiDAR on autonomous vehicle platforms by fusing detected objects from individual sensors through a late fusion approach. In the case of object detection using camera sensor, YOLOv3 model was employed as a one-stage detection process. Furthermore, the distance estimation of the detected objects is based on the formulations of Perspective matrix. On the other hand, the object detection using LiDAR is based on K-means clustering method. The camera and LiDAR calibration was carried out by PnP-Ransac in order to calculate the rotation and translation matrix between two sensors. For Sensor fusion, intersection over union(IoU) on the image plane with respective to the distance and angle on world coordinate were estimated. Additionally, all the three attributes i.e; IoU, distance and angle were fused using logistic regression. The performance evaluation in the sensor fusion scenario has shown an effective 5% improvement in object detection performance compared to the usage of single sensor.

• Journal of the Korea Fashion and Costume Design Association
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• v.20 no.4
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• pp.17-30
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• 2018

This study discusses the ambivalence and ambiguity in the relationship between the women's body and fashion drawings in respect to post-feminism perspectives. Deconstructivist post-feminists, perceiving the body as a passive subject, asserted that women internalize the male gaze by becoming the object of male desire, then manipulate the body to conform to that ideal. In this perspective, corsets assumed the role of the tool for forcing women's body to be obedient, restraining and suppressing the body. On the other hand, in the essentialist post-feminist perspective, which regards the women's body as an active object, insists that fashion, in its essence, is not necessarily about sex, nor is it devised to attract the male gaze. In such a viewpoint, the women's body functions as a vehicle for empowerment; by wearing corset women gain power and embraces the cultural norms of dominant beauty. As investigated in this study, the corset is both a tool for oppressing the women's body, as well as a vehicle for the voluntary expression of femininity. This ambivalence in the perception of the corset in the post-feminist theory represents the double-sided perspective in fashion as being both a subordinate construction and a powerful tool for self-expression.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1145-1148
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• 2002

This paper presents a new method which is calculated to use only three vanishing points in order to compute the dimensions of object and its pose from a single image of perspective projection taken by a camera and the problem of recovering 3D models from three vanishing points of box scene. Our approach is to compute only three vanishing points without this information such as the focal length, rotation matrix, and translation from images in the case of perspective projection. We assume that the object can be modeled as a linear function of a dimension vector ν. The input of reconstruction is a set of correspondences between features in the model and features in the image. To minimize each the dimensions of the parameterized models, this reconstruction of optimization can be solved by the standard nonlinear optimization techniques with a multi-start method which generates multiple starting points for the optimizer by sampling the parameter space uniformly.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.7
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• pp.619-628
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• 2000

Abstract Perspective views provide a powerful depth cue and thus aid the interpretation of complicated images. The main drawback of current perspective volume rendering is the long execution time. In this paper, we present an efficient perspective volume rendering algorithm based on coherency between rays. Two sets of templates are built for the rays cast from horizontal and vertical scanlines in the intermediate image which is parallel to one of volume faces. Each sample along a ray is calculated by interpolating neighboring voxels with the pre-computed weights in the templates. We also solve the problem of uneven sampling rate due to perspective ray divergence by building more templates for the regions far away from a viewpoint. Since our algorithm operates in object-order, it can avoid redundant access to each voxel and exploit spatial data coherency by using run-length encoded volume. Experimental results show that the use of templates and the object-order processing with run-length encoded volume provide speedups, compared to the other approaches. Additionally, the image quality of our algorithm improves by solving uneven sampling rate due to perspective ray di vergence.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.109-116
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• 2010

This study is intended to propose a technique that can trace objects by utilizing the multimarker method in the Marker Recognition which is a bridge way connecting virtuality and reality in complex environments or in a condition hands become obstacles. In the existing marker method, the object becomes blinking when the maker is blocked since this method relies only on single marker. However, the researcher was able to confirm the appearance of augmented object when the marker was blocked for the multiple markers replaced the blocked one. In order to implement such technique, multi-marker estimation was utilized with perspective matrix. The advantage is the fast estimation process for there is no need of other calculation. The implemented technique can detect markers and locate their positions, represent 3-D object in various circumstances.

• Journal of Educational Research in Mathematics
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• v.26 no.3
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• pp.355-370
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• 2016

This research intends to and understand a prospective teacher, Kim's mathematics lesson in the perspective of Activity Theory. In this study, Kim's mathematics lesson was explored in the aspects of subject, object, tools, division of labor, community, and rule which are main constituent of Activity Theory and Activity System suggested by $Engestr{\ddot{o}}m$. As the result of study, we discussed the phenomena such as the fluctuation between object and tool, the multi-voicedness between object, rule, outcome and student subject, and the dissonance between division of labor, community and rule were appeared in Kim's mathematics lesson as an activity system.