• Journal of the Korea Computer Graphics Society
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• v.19 no.4
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• pp.13-22
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• 2013

A motion capture system is widely used in movies, computer game, and computer animation industries because it allows for creating realistic human motions efficiently. The inertial motion capture system has several advantages over more popular vision-based systems in terms of the required space and cost. However, it suffers from low accuracy due to the relatively high noise levels of the inertial sensors. In particular, the accelerometer used for measuring gravity direction loses the accuracy when the sensor is moving with non-zero linear acceleration. In this paper, we propose a method to remove the linear acceleration component from the accelerometer data in order to improve the accuracy of measuring gravity direction. In addition, we develop a simple method to calibrate the joint axis of a link to which an inertial sensor belongs as well as the position of a sensor with respect to the link. The calibration enables attaching inertial sensors in an arbitrary position and orientation with respect to a link.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1591-1596
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• 1991

The present paper describes a method of recognizing a polyhedron employing the notion of network constraint analysis. Typical difficulties in three-dimensional object recognition, other than shading, reflection, and hidden line problems, include the case where appearances of an object vary according to observation points and the case where an object to be recognized is occluded by other objects placed in its front, resulting in incomplete information on the object shape. These difficulties can, however, be solved to a large extent, by taking account of certain local constraints defined on a polyhedral shape. The present paper assumes a model-based vision employing an appearance-oriented model of a polyhedron which is provided by placing it at the origin of a large sphere and observing it from various positions on the surface of the sphere. The model is actually represented by the sets of adjacent faces pairs of the polyhedron observed from those positions. Since the shape of a projected face gives constraint to that of its adjacent face, this results in a local constraint relation between these faces. Each projected face of an unknown polyhedron on an acquired image is examined its match with those faces in the model, producing network constraint relations between faces in the image and faces in the model. Taking adjacency of faces into consideration, these network constraint relations are analyzed. And if the analysis finally provides a solution telling existence of one to one match of the faces between the unknown polyhedron and the model, the unknown polyhedron is understood to be one of those memorized models placed in a certain posture. In the performed experiment, a polyhedron was observed from 320 regularly arranged points on a sphere to provide its appearance model and a polyhedron with arbitrarily postured, occluded, or imposed another difficulty was successfully recognized.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1202-1205
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• 2005

This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.257-262
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• 2017

The success or failure of the Korean game industry is a key issue for the creation of competent and talented human resources for the production of competent contents. The purpose of this study is to elucidate how to characterize and educate human - friendly game graphic designers with global competitiveness. The success of multi-disciplinary education will be maximized when cooperation with the responsible professors, the active will of the professor, the educational vision of the school, and real-time and active administration are supported In this study, based on the analysis of demand and supply of the human resources in the game industry, we found out that the game industry requires specialized manpower of technology-friendly game graphic designer who has the creativity, practical. application ability, and the international competency. In addition, we suggested ways of linking the curriculum with the local industries and related organizations such that they could be well educated as experts in related fields.

• Journal of Science and Technology Studies
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• v.19 no.2
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• pp.85-116
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• 2019

This research examines the characteristics of the newly emerging 'transformative innovation policy' and discusses the current status and issues of the Korean social problem solving R & D policy. Transformative innovation policy is a new paradigm that aims to transform socio-technical systems to address societal challenges. In this study, we analyzed 'the policy plan for solving social problems based on science and technology'. In the "Policy Plan", efforts are being made to establish new direction of science and technological innovation activities such as emphasis on social values, network formation of innovation actors, and spreading of social impact. But in this "Policy Plan", the perspective of transformative innovation policy is weakly reflected. The Policy Plan refers to system improvement that adds new elements to existing system, but it is not discussing system transformation. In order to develop social problem solving R & D policy from the viewpoint of the transformative innovation policy, it is necessary to construct the innovation platform deliberating vision and prospect for the socio-technical transformation.

• Journal of the Korea Institute of Building Construction
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• v.23 no.2
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• pp.165-173
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• 2023

This research proposed a model for automatically monitoring the quality of insulation adhesive application in external insulation construction. Upon case implementation, the area segmentation model demonstrated a 92.3% accuracy, while the area and distance calculation accuracies of the proposed model were 98.8% and 96.7%, respectively. These findings suggest that the model can effectively prevent the most common insulation defect, insulation failure, while simultaneously minimizing the need for on-site supervisory personnel during external insulation construction. This, in turn, contributes to the enhancement of the external insulation system. Moving forward, we plan to gather construction images of various external insulation methods to refine the image segmentation model's performance and develop a model capable of automatically monitoring scenarios with a considerable number of insulation materials in the image.

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.55-61
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• 2020

With the development of deep learning technology and advances in computing power, video-based research is now gaining more and more attention. Video data contains a large amount of temporal and spatial information, which is the biggest difference compared with image data. It has a larger amount of data. It has attracted intense attention in computer vision. Among them, motion recognition is one of the research focuses. However, the action recognition of human in the video is extremely complex and challenging subject. Based on many research in human beings, we have found that artificial intelligence-like attention mechanisms are an efficient model for cognition. This efficient model is ideal for processing image information and complex continuous video information. We introduce this attention mechanism into video action recognition, paying attention to human actions in video and effectively improving recognition efficiency. In this paper, we propose a new 3D residual attention network using convolutional neural network based on two attention models to identify human action behavior in the video. An evaluation result of our model showed up to 90.7% accuracy.

• Journal of The Korean Association of Information Education
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• v.9 no.2
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• pp.243-254
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• 2005

Along the information technology progresses, the demand for the educational application increases which derives the need for cyber education. Cyber education should take the knowledge construction model rather than the knowledge delivery model. For the educational paradigm shift by cyber education, 'Project-Based Learning' and 'Cyber Learning Community' need to be adopted. In this study, project-based cyber learning community for teacher education is developed with 5 major categories: Home(community vision, general information, project list, Q&A), project learning center(preparation for the instructional activities, group-based learning activities, presentations), meeting plaza(request for group mentoring, sharing ideas, meeting specialist, survey participating, forum participating, result presentation), references(cases of project studies, materials for project studies, materials for teacher education, general materials), management(project management, project cases, idea bank, finding partners, dialog with instructors, sharing references, sharing experiences, survey, forum).

• Korean Journal of Computational Design and Engineering
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• v.19 no.4
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• pp.356-367
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• 2014

A robotic sapatial augmented reality (RSAR) system, which combines robotic components with projector-based AR technique, is unique in its ability to expand the user interaction area by dynamically changing the position and orientation of a projector-camera unit (PCU). For a moving PCU mounted on a conventional robotic device, we can compute its extrinsic parameters using a robot kinematics method assuming a link and joint geometry is available. In a RSAR system based on user-created robot (UCR), however, it is difficult to calibrate or measure the geometric configuration, which limits to apply a conventional kinematics method. In this paper, we propose a data-driven kinematics control method for a UCR-based RSAR system. The proposed method utilized a pre-sampled data set of camera calibration acquired at sufficient instances of kinematics configurations in fixed joint domains. Then, the sampled set is compactly represented as a set of B-spline surfaces. The proposed method have merits in two folds. First, it does not require any kinematics model such as a link length or joint orientation. Secondly, the computation is simple since it just evaluates a several polynomials rather than relying on Jacobian computation. We describe the proposed method and demonstrates the results for an experimental RSAR system with a PCU on a simple pan-tilt arm.

• Journal of Satellite, Information and Communications
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• v.7 no.2
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• pp.8-12
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• 2012

Area-based stereo matchng algorithms are widely used for image analysis for stereo vision. SAD (Sum of Absolute Difference) algorithm is one of well known area-based stereo matchng algorithms with the characteristics of data intensive computing application. Therefore, it requires very high computation capabilities and its processing speed becomes very slow with software realization. This paper proposes a fast SAD algorithm utilizing SSE (Streaming SIMD Extensions) instructions based on SIMD (Single Instruction Multiple Data) parallism. CPU supporing SSE instructions has 16 XMM registers with 128 bits. For the performance evaluation of the proposed scheme, we compare the processing speed between SAD with/without SSE instructions. The proposed scheme achieves four times performance improvement over the general SAD, which shows the possibility of the software realization of real time SAD algorithm.