• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.399-404
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• 1992

Curved 3D objects represented by range data contain large amounts of information compared with planar objects, but do not have distinct features for matching to those of object models. This makes it difficult to represent and identify a general 3D curved object. This paper introduces a new approach to representing and finding a holdsite of general 3D curved objects using range data. We develop a three-dimensional generalized Hough transformation which can be also applied to general 3D curved object recognition and which reduces both the computation time and storage requirements. Our approach makes use of the relative geometric differences between particular points on the object surface and some model points which are prespecified arbitrarily and task dependently.

• 산업경영시스템학회지
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• 제23권58호
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• pp.1-16
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• 2000

To develop a generic ERP(Enterprise Resource Planning) system which can accommodate various types of manufacturing enterprises, object-oriented methods are commonly applied from analysis to implementation. The objective of OO-ERP (Object-Oriented ERP) systems is the reusability of business objects(components). In practice, one of the critical features for the reusable OO-ERP system would be the capability of interfacing with distributed, heterogeneous data repositories. Consequently, it is essential to provide data repository transparency in OO-ERP systems - business objects do not take care of the locations and types of data repositories. In this paper, we propose Data Object Layer(DOL) that supports such transparency. DOL is a horizontal component through which OO-ERP systems can be seamlessly connected with diverse data repositories.

• 한국통신학회논문지
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• 제34권3C호
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• pp.274-278
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• 2009

히스토그램에 의한 객체 유형 인식 방법은 최근 들어 많은 연구가 이루어지고 있다. 그러나 대부분의 히스토그램 기반의 객체 추적이 칼라 모델을 사용하여 견실성을 개선하였지만 아직 충분히 견실하다고 할 수 없다. 이러한 단점을 보안하기 위하여 본 논문에서는 연속적인 프레임에서 히스토그램을 이용하여 객체를 표현하고 추적하는 방법을 제시하고자 한다. 자동차를 대상으로 실험한 결과 80m 거리 이내에서 신뢰성 있는 방법임을 확인하였다.

• 전기학회논문지
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• 제59권2호
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• pp.429-435
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• 2010

Three dimensional (3-D) object detection and pose estimation from a single view query image has been an important issue in various fields such as medical applications, robot vision, and manufacturing automation. However, most of the existing methods are not appropriate in a real time environment since object detection and pose estimation requires extensive information and computation. In this paper, we present a fast 3-D object detection and pose estimation scheme based on surrounding camera view-changed images of objects. Our scheme has two parts. First, we detect images similar to the query image from the database based on the shape feature, and calculate candidate poses. Second, we perform accurate pose estimation for the candidate poses using the scale invariant feature transform (SIFT) method. We earned out extensive experiments on our prototype system and achieved excellent performance, and we report some of the results.

• International Journal of Advanced Culture Technology
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• 제8권4호
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• pp.119-128
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• 2020

Object detection is an important field of computer vision and is applied to applications such as security, autonomous driving, and face recognition. Recently, as the application of artificial intelligence technology including deep learning has been applied in various fields, it has become a more powerful tool that can learn meaningful high-level, deeper features, solving difficult problems that have not been solved. Therefore, deep learning techniques are also being studied in the field of object detection, and algorithms with excellent performance are being introduced. In this paper, a deep learning-based object detection algorithm used to detect multiple objects in an image is investigated, and future development directions are presented.

• 한국멀티미디어학회논문지
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• 제24권2호
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• pp.167-177
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• 2021

In the field of augmented reality, edge-based methods have been popularly used in tracking textureless 3D objects. However, edge-based methods are inherently vulnerable to cluttered backgrounds. Another way to track textureless or poorly-textured 3D objects is to directly align image intensity of 3D object between consecutive frames. Although the direct methods enable more reliable and stable tracking compared to using local features such as edges, they are more sensitive to occlusion and less accurate than the edge-based methods. Therefore, we propose a method that combines an edge-based method and a direct method to leverage the advantages from each approach. Experimental results show that the proposed method is much robust to both fast camera (or object) movements and occlusion while still working in real time at a frame rate of 18 Hz. The tracking success rate and tracking accuracy were improved by up to 84% and 1.4 pixels, respectively, compared to using the edge-based method or the direct method solely.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.51-59
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• 2024

In this work, we focused on reducing the amount of image data to be sent by extracting and progressively sending prominent image features to high-performance computing systems taking into consideration the right amount of image data required by object identification application. We demonstrate that with our technique called Progressive Object Detection over a Lossless Network using Fragmented DCT Coefficients (Proficient), object identification applications can detect objects with at least 70% combined confidence level by using less than half of the image data.

• 한국시뮬레이션학회논문지
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• 제3권1호
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• pp.151-165
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• 1994

Broadband network based on the Asynchronous Transfer Mode(ATM) concept are becoming the target technology for the emerging Broadband Integrated Services Digital Network(B-ISDN). Since B-ISDN is very complex and requites a great amount of investment, optimum design and performance analysis of such systems are very important. Simulation can be widely used to analyze and examine the broadband network behavior. However, for the complicated system like broadband networks it is extremely difficult and time-consuming to develop a complete model for simulation. In this paper, an object-oriented modeling approach for the broadband network simulation is presented for the effective and efficient modeling. Object-oriented approaches can provide a good structuring capability for complicated simulation models and facilitate the development of reusable and extensible simulation models. We have developed an object-oriented model which consists of object model and behavior model. In the object mode., the components of the broadband network and both constant bit rate(CBR) and variable bit rate(VBR) traffic types of call level, burst level, and cell level are modeled as object classes. In the behavior model, the dynamic features for each object class are represented using the state transition diagram. It has been shown by illustration that objectoriented modeling is an effective tool for modeling the complicated B-ISDN.

• 제어로봇시스템학회논문지
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• 제21권10호
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• pp.958-964
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• 2015

In this paper, an object recognition method based on the depth information from the RGB-D camera, Xtion, is proposed for an indoor mobile robot. First, the RANdom SAmple Consensus (RANSAC) algorithm is applied to the point cloud obtained from the RGB-D camera to detect and remove the floor points. Next, the removed point cloud is classified by the k-means clustering method as each object's point cloud, and the normal vector of each point is obtained by using the k-d tree search. The obtained normal vectors are classified by the trained multi-layer perceptron as 18 classes and used as features for object recognition. To distinguish an object from another object, the similarity between them is measured by using Levenshtein distance. To verify the effectiveness and feasibility of the proposed object recognition method, the experiments are carried out with several similar boxes.

• 한국실내디자인학회논문집
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• 제24권2호
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• pp.67-77
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• 2015

This study is to contemplate an ultimate goal and new methodology the architecture and space design community should pursue forward by analyzing concepts in Kengo Kuma's idea of "Anti-object" and examining his design methods and characteristics. To this end, I reviewed space design methods and features in his book of "Anti-Object" and his architectures built around in 2000. The result is as in the followings. (1) Contact is an essential concept of "Anti-object" to connect and integrate divided materials and consciousness with time and space. (2) Elimination is a meaningful way to reverse "cohesiveness" of agglomerated cluster which is a form of object and reconstruct it into the form of passive and acceptive "Anti-object". This idea is realized through overlap of material property and removal of massing. (3) Minimization is a concept of "Anti-object" to set the temporality free from constraints of materials. Three-dimensional transparent faces and lines or patterns of porous materials can be used to remove static and coercive volume. (4) A particle is a "reflector of its environment." It rebuilds one-way or disconnected communication between human and architecture into an interactive one. Kengo Kuma materializes this "particle" by exploring positional relation with physical paths, precise details and measurements.